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This PDF file contains the front matter associated with SPIE Proceedings Volume 8335, including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.
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Proceedings of 2012 International Workshop on Image Processing and Optical Engineering
The electro-optic effects in silicon include Kerr effect, plasma dispersion effect, and Franz-Keldysh effect etc.. Silicon
does not have the linear electro-optic effect in the bulk because of the inversion symmetry, which restricts the
development of the silicon-based optoelectronics and silicon photonics. However, the electric field can destroy the
inversion symmetry of silicon, and produce so-called electric-field-induced linear electro-optic effect. In intrinsic or
near-intrinsic silicon, these electro-optic effects exist simultaneously. In this paper, a transverse electro-optic modulation
system was designed to detect these electro-optic effects. The electric-field-induced linear electro-optic effect was
demonstrated in the space charge region of silicon sample and distinguished from Kerr effect based on the different
frequency response. The relationship between the linear electro-optic signal and the azimuth angle of the analyzer was
measured too, which was used for distinguishing the electric-field-induced linear electro-optic effect from the plasma
dispersion effect. The results showed that the electric-field-induced linear electro-optic effect was stronger than Kerr
effect and the plasma dispersion effect in the near-intrinsic silicon samples.
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The features of the spatial information of Markov random field image was used in image segmentation. It can effectively
remove the noise, and get a more accurate segmentation results. Based on the fuzziness and clustering of pixel grayscale
information, we find clustering center of the medical image different organizations and background through Fuzzy cmeans
clustering method. Then we find each threshold point of multi-threshold segmentation through two dimensional
histogram method, and segment it. The features of fusing multivariate information based on the Dempster-Shafer
evidence theory, getting image fusion and segmentation. This paper will adopt the above three theories to propose a new
human brain image segmentation method. Experimental result shows that the segmentation result is more in line with
human vision, and is of vital significance to accurate analysis and application of tissues.
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Thanks to the exceptionally good properties in chaotic systems, such as sensitivity to initial conditions and control
parameters, pseudo-randomness and ergodicity, chaos-based image encryption algorithms have been widely studied and
developed in recent years. A novel digital image encryption scheme based on the chaotic ergodicity of Baker map is
proposed in this paper. Different from traditional encryption schemes based on Baker map, we permute the pixel
positions by their corresponding order numbers deriving from the approximating points in one chaotic orbit. To enhance
the resistance to statistical and differential attacks, a diffusion process is suggested as well in the proposed scheme. The
proposed scheme enlarges the key space significantly to resist brute-force attack. Additionally, the distribution of gray
values in the cipher-image has a random-like behavior to resist statistical analysis. The proposed scheme is robust against
cropping, tampering and noising attacks as well. It therefore suggests a high secure and efficient way for real-time image
encryption and transmission in practice.
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Intrinsic bistability in active optical compounds doped with rare-earth ions has attracted widespread interest because of
its relevance for optical signal switching and routing. In this paper, room temperature strong bistability effect of Ybsensitized
Tm upconversion emission is reported in zirconium dioxide nanocrystal host matrix under infrared diode laser
irradiation. The distinct optical bistability behavior is simultaneously observed in three emission bands of Tm ion around
480, 650/680 and 800 nm which are assigned to the radiative transitions of 1G4→3H6, 1G4→3F4/3F2,3→3H6, and 3H4→3H6,
respectively. The bistability loops exhibit uniformly clockwise cycle characterized by a relatively lower trace of emission
intensity at decreasing pump power than the trace at increasing pump power. Multiphoton upconversion processes are
analyzed to determine the Yb→Tm energy transfer mechanism. Such strong bistability effect is associated with
thermally enhanced nonradiative decay and reduced luminescence quantum yield due to the strong pump-induced local
thermal loading.
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The weakening groove becomes the weaker link in separating unit since it bears axial load, bending moment and shearing
force during operating. The strain distribution of weakening groove is obtained by ARAMIS system based on 3D digital
speckle correlation method (DSCM). The result indicates that there is stress concentrate band in each groove, and the strain
increased from the lower one to the upper ones. The result also demonstrates that the ARAMIS system performed with
good results, especially in 3D deformation and stress concentrate measurement.
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Skeletal age has been studied and proved that for most elite athletes, it was coincident with the chronological ages when
they were young. In order to explore the application of skeletal age in selecting sports talent, 32 athletes (female,
chronological age 5-12 y) were chosen from the Gymnastics Training Base in this study. Their left hand-wrists were
photographed with X-rays, and then the skeletal ages were estimated by Chinese version of the Tanner-Whitehouse
Skeletal Maturity Assessment System. At the same time, their body shapes, functions, and sports ability were also
measured. Results showed that 71.88% of the skeletal age was proportional to their chronological age (± 1 y); while
18.75% of the skeletal maturity was retarded by 1- 2 year, 9.37% of those was advanced more than 1 year. On the other
hand, the body shape, functions and sports ability of the athletes were positively related with their skeletal maturity. This
study proved that the determination of skeletal maturity is a reliable evaluation for selecting sports talent. A further study
on the influence of gymnastics on the skeletal age is of great significance.
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With the development of power technology and the expansion of power plants, plant operation monitoring points are increasing at
the same time. A large number of data parameters let technicians obtain more information about unit running, but adjusting and
processing the data processing are inconvenient. Principal Component Analysis was used for the real-time data analysis in the thermal
power plant unit running. New variables can be obtained from the multi-parameter indicators by knowledge mining. Since the new
variables are pairwise uncorrelated which can reflect most of original data information, they can provide the basis for optimal
operation and adjustment of the actual production units. It will also play an important role in the factory data processing and related
fields.
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White light interferometry(WLI) has grown to be a standard measurement method in the field of micro/nano manufacture.
Vertical white light scanning interferometry(VSI), tilt white light scanning interferometry(TSI) and white light phase
shifting interferometry(WLPSI) are introduced in this paper. A new algorithm based on the combination of VSI and
image segmentation technology for measuring the film is presented in this paper. TSI is taken place of VSI for expanding
its lateral measuring range and improving the testing efficiency as the vertical and lateral information of the samples are
obtained after one time scan. Carré phase shifting is combined with vertical white light scanning which formed a white
light phase shifting method. The measurement system equips a Mirau microscopic interferometer, and the scanning
process is driven by nano-measuring machine(NNM) which is a high precision nano-positioner. At last, the testing results
of some micro-structures illustrate the capabilities of the proposed algorithms.
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Network tutoring system is currently a popular research subject in the world. And with the development of artificial
intelligence technology, the intelligent tutoring strategy theory has been improved a lot. This paper makes use of the
theory of multi-agent plan to develop the model of network tutoring strategic decision-making system, and improves the
efficiency of the decision-making system and the continuity of the system to make decisions by the multi-agent plan. It
also coordinates and improves the dynamic timeliness of the decision-making system by the multi-agent, and ensures the
decision-making system to obtain the best results in the overall situation.
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We present an automatic road sign detection and recognition service system for mobile devices. The system is based on a
client-server architecture which allows mobile users to take pictures of road signs and request detection and recognition
service from a centralized server for processing. The preprocessing, detection and recognition take place at the server
end and consequently, the result is sent back to the mobile device. For road sign detection, we use particular color
features calculated from the input image. Recognition is implemented using a neural network based on normalized color
histogram features. We report on the effects of various parameters on recognition accuracy. Our results demonstrate that
the system can provide an efficient framework for locale-dependent road sign recognition with multilingual support.
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Within the Section of Astronomy of the Department of Physics and Astronomy of the University of Firenze (Italy), the
XUVLab laboratory is active since 1998 dedicated to technological development, mainly UV oriented. The technological
research is focused both on electronics and optics. Our last approach is dedicated to the development of innovative wiregrid
polarizers optimized to work in transmission at 121.6 nm. The manufacturing of such optical devices requires
advanced technological expertise and suitable experimental structures. First, nanotechnology capability is necessary, in
order to build several tiny parallel conductive lines separated by tens of nanometers on wide areas to be macroscopically
exploitable in an optical laboratory. Moreover, the characterization of such an advanced optical device has to be
performed in vacuum, being air absorptive at 121.6 nm. A dedicated small vacuum chamber, SCOUT (Small Chamber
for Optical UV Tests) was developed within our laboratory in order to perform practical and fast measurements. SCOUT
hosts an optical bench and is equipped with several opening flanges, in order to be as flexible as possible. The flexibility
that has been reached with SCOUT allows us to use the chamber beyond the goals it was thought for. It is exploitable by
whatever compact (within 1 m) optical experiment that investigates the UV band of the spectrum.
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In this paper we perform an applied comparative study of popular HOG based human detection and a state-of-the-art
pose adaptive method that uses shape-based model construction. Both methods are implemented with kernel SVM,
instead of linear SVM. Detailed performance evaluation is carried out on MIT pedestrian dataset and INRIA person
dataset. This study shows that, although pose adaptive method has no significant advantage compared to the HOG based
approach on those datasets, the pose adaptive approach is more efficient in detection and it has the capability to segment
the human shape from images while carrying out detection which can be advantageous in many applications.
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Face recognition has broad applications, and it is a difficult problem since face image can change with photographic
conditions, such as different illumination conditions, pose changes and camera angles. How to obtain some invariable
features for a face image is the key issue for a face recognition algorithm. In this paper, a novel tensor structure of face
image is proposed to represent image features with eight directions for a pixel value. The invariable feature of the face
image is then obtained from gradient decomposition to make up the tensor structure. Then the singular value
decomposition (SVD) and principal component analysis (PCA) of this tensor structure are used for face recognition.
The experimental results from this study show that many difficultly recognized samples can correctly be recognized,
and the recognition rate is increased by 9%-11% in comparison with same type of algorithms.
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Based on the principle of non-imaging optics, the illumination system with the laser diode (LD) array is designed for
new laser projection system in this paper. Both illumination system designs of the light pipe and fly's eye lens array are
presented using standard optical design software Zemax, including the shaping design of laser source beam, uniform
light system design and the relay lens design. Good performances are achieved in the simulation. Energy efficiencies of
two designs are ⪆65% and both of beam uniformities are near to 96% in the illumination system.
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The principle of Fourier plane filtering in coherence probe microscopy (CPM) is demonstrated. It is shown that an edge
contrast enhancement can be obtained in an isotropic and anisotropic way for different technical materials containing
interfaces or internal micro-structures. Additionally image processing completes the CPM imaging and analysis.
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Combo-biding is uncertain game-collaborative with uncertainty,and decision maker's experience is fuzzy.Gameoptimizing
of combo-biding can be translated into fuzzy-chance- restriction programming according to Fuzzy Bernardo
Methed with a view to creditability measure of fuzzy occurrence.The method can adapt itself to game-collaborative
decision-making of combo-biding in allusion to different gaol.
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A NDVI detector is developed based on ground-based remote sensing, which uses proper wavebands and embeds a new
optimization algorithm of nitrogen fertilization. The detector has two main units, optical unit and electronic unit. In
optical unit there are four special different photoelectrical sensors used for detecting sunlight incidence and reflect light
of plant canopy in red and NIR wavebands, respectively. Analog signals measured by sensors are amplified and then
converted to digital in electronic unit. After processing the digital signal, NDVI of the plant can be calculated.
Performance and stability experiments are conducted to cucumber plants in greenhouse. The results show that the
detector has a good stability. In order to eliminate the error from sunlight a new artificial light source is suggested.
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Machine vision has been widely applied in facility agriculture, and played an important role in obtaining environment
information. In this paper, it is studied that application of image processing to recognize and locate corn tassel for corn
detasseling machine. The corn tassel identification and location method was studied based on image processing and
automated technology guidance information was provided for the actual production of corn emasculation operation. The
system is the application of image processing to recognize and locate corn tassel for corn detasseling machine.
According to the color characteristic of corn tassel, image processing techniques was applied to identify corn tassel of
the images under HSI color space and Image segmentation was applied to extract the part of corn tassel, the feature of
corn tassel was analyzed and extracted. Firstly, a series of preprocessing procedures were done. Then, an image
segmentation algorithm based on HSI color space was develop to extract corn tassel from background and region
growing method was proposed to recognize the corn tassel. The results show that this method could be effective for
extracting corn tassel parts from the collected picture and can be used for corn tassel location information; this result
could provide theoretical basis guidance for corn intelligent detasseling machine.
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Feature selection is the core research topic in text categorization. Selected feature subset directly influences
results of text categorization. Firstly, word frequency and document frequency were analyzed. And then, the category
concentration degree based on word frequency and document frequency was proposed. Next, set covering was
introduced into rough sets and an attribute reduction algorithm based on minimal set covering was provided. Finally, a
new feature selection method combined the proposed category concentration degree with the provided attribute reduction
algorithm was presented. The presented feature selection method firstly uses the proposed category concentration degree
to select features and filter out some terms to reduce the sparsity of feature spaces, and then employs the provided
attribute reduction algorithm to eliminate redundancy, so that the more representative feature subset was acquired. The
experimental results show that presented feature selection method is better than the three classical feature selection
methods: information gain (IG), x2 statistics (CHI), mutual information (MI) in time performance, macro-average
F1 and micro-average F1.
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This paper gives a non-destructive and non-contact inspection way based on image processing which
is introduced to detect bridge cracks. System architecture is also introduced and key algorithms in
crack image processing is studied. These key algorithms are: image gray scaling, image
enhancement, image strengthing, gap survey and so on. In the end such method is used to measure
actual gap and the reliability of such method on bridge inspection has been verified with the results.
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Target recognition is more difficult for the distortion space target images coming from view, camera, climate et al. It is a
effective method to recognize target with moment feature for its translation invariance, rotation invariance and scale
invariance. This paper studied the features and application conditions on Hu's moments, affine invariant moments, and
wavelet invariant moments, made combined moments for target recognition. It combines partial Hu's moments, affine
invariant moments with wavelet invariant moments. To take ship target recognition for an example, the combined
moments is proved suitable for improving recognition efficiency by Matlab simulation.
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Existing image pyramid data structures have certain limitations. Some need much more storage space than
original images; some are unable to reconstruct original images accurately; the others result in bad visual qualities. In
this paper, a type of modified reduced-sum pyramid (MRSP) is proposed. In such a pyramid, every father-node can be
got by adding a certain integer to one of its son-nodes, and the son-node can also be got by subtracting the same integer
from the father-node. This integer is calculated using the neighboring nodes of the son-node. This type of pyramid has
many possible implementations; they all fulfill the same general formula, but use different approaches to calculate the
integer. One implementation, based on the technique of image inpainting, is also presented in this paper. Theoretical
analysis and experiments demonstrate that the proposed pyramid achieves good performance in precision, storage space
and visual quality.
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In view of low sensitivity of CCD arrays in the ultraviolet range, a new measuring method for ultraviolet spectrum with a
32-anode linear photomultiplier tube (PMT) array is presented. A spectrum measurement system that includes a
spectroscopic design and data acquisition circuits, together with the system-controlling software, has been developed for
the PMT array. Compared with a spectrometer which employs a back-thinned CCD with the highest ultraviolet
sensitivity, experiments indicate that the system has the same sensitivity as the spectrometer which works at the
integration time of about 2 s, while requiring less than 7 ms for one single measurement. It is able to perform timeresolved
measurements even in weak light applications where CCD spectrometers need to work at long integration times.
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A binocular vision system and its application to face detection and tracking in robot is introduced in this paper. With the
vision system, the robot can do face detection, identification, recognition and tracking. The face area is detected in realtime
by using AdaBoost algorithm. And a method is proposed with which a real face can be distinguished from a picture
one by using skin color information and depth data. A specific face can be recognized by comparing the principal
components of the current face to those of the known individuals in a face database built in advance. Finally, the robot
can track a specified face according to depth of the face and position of a face rectangle in the frame. Experiment results
are given and discussed.
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Because of the physical constraint of the spatial information sensor, there is a tradeoff between the spatial and spectrum
resolution of remote sensing image. A region-based regression model is presented to fuse panchromatic and multispectral
images. The upsampled MS image is segmented into isolated regions firstly. Then, a regression model is established
independently for each isolated region by considering the linear relationship between corresponding PAN and MS image
pixel values in the region. Finally, a modulation-based fusion technique is employed to get fusion result. The method is
compared with the Brovey method and the fusion based global regression in both qualitative and quantitative ways,
shows superior result.
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The paper put forward the system error evaluation method of 3D scanning system for gangue monitoring; analyzed
system errors including integrated error which can be avoided, and measurement error which needed whole analysis;
firstly established the system equation after understanding the relationship of each structure. Then, used error
independent effect and spread law to set up the entire error analysis system, and simulated the trend of error changing
along X, Y, Z directions. At last, it is analytic that the laser rangefinder carries some weight in system error, and the
horizontal and vertical scanning angles have some influences on system error in the certain vertical and horizontal
scanning parameters.
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An experiment with EIZO CG 19, DELL 19, IBM 19 and HP 19 LCD was designed and carried out to test the
interaction between RGB channels, and then to test the spectral additive property of LCDs. The results show that the
interaction between channels is very weak and spectral additivity is held well. This result indicates that the manufacture
technology of LCDs is improved greatly. But the computation results of tristimuli addition are not very accurate. A new
calculation method based on spectral additivity, in which gamma is fitted by a cubic polynomial in each piece of
wavelength, is proposed and discussed. The proposed method is proved simple and very few samples need to measure
while the computation precision is very high.
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A laser automatic tracking extensometer for material deformation measurement based on CCD is proposed. The image
processing methods of the laser mark localization and the automatic tracking of the mark line on the specimen are
studied for the extensometer. First, geometrical mean filter (GMF), harmonic mean filter (HMF) and inverse harmonic
mean filter (IHMF) using for the image processing are compared in order to select a suitable mean filter for removing
noises from the specimen images, and then the GMF is adopted for the de-noising of the images. Second, Sobel operator
is introduced to detect the edges of the specimen images. At last, the specimen images are reduced to eliminate unwanted
background information by pruning. Hough transformation of pretreated specimen images is also studied and linking
images algorithm is proposed based on the image gray distribution and the connectivity principle. The laser mark
localization and the automatic tracking of the mark line on the specimen are then implemented. The experimental results
show that the linking image algorithm is prior to Hough transformation on both recognition effect and recognition
efficiency.
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In order to solve the problem of false matches generated from the similar region in image matching, In this paper, an
algorithm for a robust image matching method based on the combination of the improved Shape context method and
SIFT is proposed. First we extracted the key points and matching them using SIFT. Then we exploited the rotation and
scale information from matched SIFT key points, K-means Clustering can estimate the ratio scale and rotation angle
accurately and with which we achieve the rotation and scale invariant shape context. Finally The matches is obtained by
Shape Context Matching. Experiment show that, the algorithm can improve the accuracy of matching.
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A series of printed samples on substrate of semi-gloss paper and with the magnitude of threshold color difference were
prepared for scaling the visual color difference and to evaluate the performance of different method. The probabilities of
perceptibly was used to normalized to Z-score and different color differences were scaled to the Z-score. The visual
color difference was got, and checked with the STRESS factor. The results indicated that only the scales have been
changed but the relative scales between pairs in the data are preserved.
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An experiment was carried out under different light illuminance to verify the failures of color additivity and color
adaption transformation. In the asymmetric color matching experiment, many matched monitor colors are "bluer" than
the printed colors placed in the cabinet. The color additivity and adaption failures have practical consequences in
cross-media color matching. Different modification in different color region was used in the color adaption
transformation and the shift between the printed and monitor samples have been corrected to some extent. In order to
modify the color matching functions and improve the color adaption transformation, more experimental data were
required in the further research.
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Image denoising with second order partial differential equations (PDEs) often leads to undesirable staircase effect,
namely, the transformation of smooth regions into piecewise constant regions. In this paper, staircase effect is analyzed
in spatial frequency domain which is different from previous studies. A method of nonlinear diffusion based on
Laplacian Pyramid is proposed. The experimental results show that the proposed method alleviates the staircase effect
and leads to more natural restored images.
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We propose the concept of axially symmetric polarized beams as an extension of radially and azimuthally polarized
beams, and study the focusing properties and applications of higher polarization order axially-symmetric polarized
beams. We present the mathematical expressions of the focusing field in an aplanatic focusing system and numerically
calculate the focusing field distributions near focus, and find out some unique focusing properties, especially multiplefocus-
spot super-resolution focusing, which will lead to some applications in super-resolution, multiple particles
manipulation, near-field microscopy and so on.
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Piston ring is one of the most important parts in internal combustion engine, and the width of end gap is an important
parameter which should be detected one by one. In comparison to the previous measurements of end gap, a new efficient
detection method is presented based on computer vision and image processing theory. This paper describes the
framework and measuring principle of the measurement system. In which, the image processing algorithm is highlighted.
Firstly, the partial end gap image of piston ring is acquired by the area array CCD; secondly, the end gap edge contour
which is connected by single pixel is obtained by grayscale threshold segmentation, mathematical morphology contour
edge detection, contour trace and other image processing tools; finally, the distance between the two end gap edge
contour lines is calculated by using the least distance method of straight-line fitting. It has been proved by the repetitive
experiments that the measurement accuracy can reach 0.01mm. What's more, the detection efficiency of automatic
inspected instrument on parameters of piston ring based on this method can reach 10~12 pieces/min.
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In-line phase contrast imaging using micro-focus x-ray source is an important diagnostic tool in medicine, biology and
materials science. The phase retrieval enables us to obtain material information from the gray of the phase-contrast
image. A phase retrieval algorithm based on phase-attenuation and Fourier-wavelet regularization was proposed, which
only need one single projection image and can deal with the case of large Fresnel propagator corresponding to high
spatial resolution imaging. And the energy response function of detector and x-ray spectral density distribution of source
were considered in this algorithm. The effectiveness of the proposed approach was tested by experimental image of silica
aerogel.
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To improve the reliability and accuracy of iris-based identification system, this paper proposed an efficient method based
on multi-level fusion. Multi-level fusion contains two levels: multialgorithmic fusion and multiinstance fusion. The
multialgorithmic fusion integrates the improved phase algorithm and the DCT-based algorithm, and the multiinstance
fusion combines information from left iris and right iris of an individual. Both multialgorithmic fusion and multiinstance
fusion are carried out at the matching score level. The experimental results on the noisy iris database UBIRIS
demonstrate that the proposed fusion schemes can perform better than the simple recognition systems.
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In this paper, we design a high power and small volume laser source module using the laser diode array for the laser
projector system. This module can efficiently suppress speckle noise by reducing the phase coherence using laser diode
array. In addition, we use the rotating diffuser to further disturb the coherence of the lasers for lower speckle noise. The
experimental results show that the laser source module and the rotating diffuser can effectively eliminate the speckle
noise. This new light module with laser diode array can be used in the laser projection system with high brightness,
small volume and low speckle noise.
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A wide-field-of-view broad-band spectral filter with polarization function is presented for skylight polarization detection.
The designed structure consists of a nanowire grating and a multilayer dielectric band pass filter. The simulation based
on the rigorous coupled wave analysis shows that with the optimized uppermost layer of the dielectric filter or the
addition of the PMMA layer, the desired integration performance can be achieved. The grating parameters are
thoroughly investigated using rigorous coupled wave analysis and effective medium theory. The TM transmission higher
than 80% and the extinction over 500 can be achieved in the range of 380nm to 520nm, up to ±35° wide incident angle,
and extremely low transmission for both TM and TE polarization in the other spectral range are also obtained.
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In this paper, we design a high power and small volume laser projector using the red laser diode, green laser diode, blue
laser diode and green fluorescence as light source, which could improve the performance of the projector significantly
with longer lifetime than lamps, higher reliability, and larger color gamut. According to the requirement of CIE Standard
Illuminant D65 and light output, the power of red laser diode, green laser diode, blue laser diode and green fluorescence
were calculated. The energy efficiency of four base-color optical path was also analyzed. It could be concluded that the
blue laser and red laser have higher power requirements.
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In combination with the discrete wavelet transform (DWT), set partitioning in hierarchical trees (SPIHT) is one of the
most renowned techniques for image compression. One problem with SPIHT, however, is that its decoding can be
extremely sensitive to errors in its embedded bit stream. In this paper, we address the issue of transmitting SPIHTencoded
images in packets via erasure channels, wherein each received packet is either error-free or totally discarded. In
our scheme, the original SPIHT code sequence is packetized (into two types: critical packet (CP) and refinement packet
(RP)). Those packets are then allocated with different diversity orders for unequal error protection (UEP) so that the
decoded image is expected to attain the highest signal-to-noise ratio (SNR) at the receiver. Simulations show that the
proposed scheme significantly improves the decoded images as compared to the case of no diversity allocation and the
case of not distinguishing between CP and RP.
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A new method for image registration based on step-by-step registration is proposed. First, SIFT feature algorithm is used to
image to get rough registration then optical flow algorithm is used to achieve the final accurate registration. Image feature
point extraction is the basis of medical image registration and its accuracy impacts on the matching results directly. SIFT
feature algorithm is based on local image features and has a good feature of scale, rotation, illumination invariant. Optical
flow algorithm no need to do feature extraction and this method calculation is quick and simple and it uses image intensity
information directly. The two steps are complementary that the former prepare for the latter to improve the convergence
rate while the latter allows a more accurate registration result. The experimental results show that this algorithm can
improve the efficiency of non-rigid medical image registration accuracy and increase convergence speed thus it has certain
superiority in terms of image registration.
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Many ancient sites of different cultural period distributed in the Taihu lake basin. The natural environment is the material
foundation that the mankind relies for existence and development, so it's necessary to master the natural environment at
that time in order to understand the culture of site. The paper analyzed morphological characteristics and temporal and
spatial distribution of ancient site using GIS spatial analysis method which based on the remote sensing image and DEM
data. Some terrain indexes were selected as the evaluation factor including altitude, slope, aspect, slope shape and
surface rolling, which were used to analyze the relation between the spatial location of ancient site and the natural
environment. The research shows the spatial location of ancient sites have a close relationship with natural environment
by the terrain analysis and hydrological analysis. Especially, the water distribution plays an important role in the
constraints of the distribution of ancient sites, meanwhile the ancients showed the capacity to adapt the environment.
Throughout the development of the ancient sites, ancients and nature depend on each other for existence.
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A chip visual localization method based on vision for IC packaging equipment was developed to satisfy the high
precision requirement in the chip inspection in this paper. The method is based on the combination of Hough transform
and prior geometric knowledge of chip. First, a straight line was extracted to match chip image.Then the conversion
function of the chip image was deduced based on the straight line endpoint coordinates. Because the relative position
coordinates of chip corner are known, the other two endpoints of chip in image can be deduced with substituting the
known model coners coordinates into the matching conversion function. Finally, the chip orientation is achieved by
linking the corners coordinates. Experimental results have shown that the the chip can be orientated accurately using this
method.
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We propose a similarity-based learning style algorithm by regarding each image as a multi-instance (MI) sample for
image classification. An image featured as vectorial representation interesting regions is transferred to a MI sample.
Then a similarity like matrix is constructed using MI kernel between given images and some carefully selected base
images, as the new representation of given images. Three selection strategies are proposed to build the base images set to
find an optimal solution. A Weka implementation decision tree is used as the main learner in this paper. Experiments on
image data repository ALOI and Corel Image 2000 show the effectiveness of the proposed algorithm compared to some
previous based line methods.
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Shots classification plays an important role in well indexing, browsing and retrieving video content. By
that, the large amount of video content can be efficiently indexed, and then, it can provide convenience
for managing video. In this paper, edge features are firstly extracted by wavelet, which can not only
reduce amount of shots data but also preserve the important structural properties of shots. And then, to
reflect local properties of shots, ratio of edge pixels in each sub-window is calculated. After that, color
moments are computed to reduce loss of global properties, which can assist edge features in well
indexing shots. Finally, support vector machine (SVM), which has a very good performance on pattern
recognition, is employed to classify shots. Experimental results demonstrate that this method can
efficiently categorize video shots and satisfy the basic needs of shots classification.
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A single-wavelength Brillouin fiber ring laser is presented and its characteristics are investigated experimentally. The
pump wavelength is 1551.8nm, and the length of the fiber in the ring cavity is about 13km. The influence of the pump
and the output coupler on the laser output spectrum is discussed. The results show that high output coupling ratio leads to
high power of output laser. When the power of the pump is over -12.8dBm, an obvious stimulated Brillouin scattering
peak is acquired. The laser has low threshold, and is proved to be stable with power fluctuations of less than 0.7dB over
more than 1h.
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With the cross-disciplinary development of agent technology and war simulation technology, there are many problems
when classical BDI logic is used in war simulation. Aiming at the characteristic of agent in war simulation, the BDMIVSK-
T model frame is built, which combines with classic BDI-VSK-T model and imports a non-normal modal operator
mission. Basic axioms and interaction axioms in BDMI-VSK-T logic are discussed and its soundness and completeness
are proved. It is also proved that operator mission avoid the side-effect and the logical omniscience problem.
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In this research we present a new method for image compression which is a combination of lossy and lossless image
coder .In lossy part we use a 3-level decomposition of discrete wavelet transform with hard threshold technique. lossless
image coding part is Burrows Wheeler Transform (BWT) which has received considerable attention in recent years
because of its simplicity and effectiveness. The BWT is used with other additional methods of image compression such
as, MTF, RLE and entropy coding algorithms. the effectiveness of over method is presented and compare with JPEG and
JPEG2000 for different images concidering criteria such as PSNR ,Compression Ratio (CR) and images quality(HVS)
in our future works we use BWT with other source coding algorithm such as Lempel-Ziv and different mother function
for DWT.
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In optical test technology, the optical parameters measurement is common. Different optical parameters of the
optical system represent the different characteristics. The accuracy and precision of optical parameters measurement are
influencing the performance evaluation directly. Sphere radius which is decided the optical properties is a main
parameter of lens. But the traditional measuring method has many problems. There are testing cost, contact
measurement, the required test pieces, test range, accuracy and so on. Therefore, it is necessary to find out a lowertesting
cost, higher precision and non-contact measurement method. According to the shortcomings and deficiencies in
radius measurement, a fast, high-efficient, intelligent way has been researched. This paper proposes a measuring method
of radius based on the image analysis. Processing with MATLAB is used for dealing with the collected image. Two
points are gained by auto-collimation. The radius is the difference between the vertex and centre of sphere. Conduct the
experiments separately with plane convex lens and plane concave lens. The experimental results indicate that the
measurement method presented in this paper have less than ±0.15% relative error and ±0.25% repeatability.
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The importance of space scale matching of flying direction and object long axis is presented when we measure
nutation angle of flying object with slit photography, and a new method to measure nutation angle of flying object
combined slit photography and double linear CCD intersection is examined. A brief methodology of nutation angle
computing by series double linear image analysis is discussed, and a nunation angle measurement system is designed. A
series linear image analysis method is developed to obtain the image position of series point on object long axis at pixel
scale, and then the double linear CCD intersection theory is used to find the space coordinate position of various points
at actual space scale. They are also put forward in this paper that invalid coordinate data are rejected by line detecting
and flying direction data space is decided by perpendicular flying distance of object at CCD sampling interval. At final, a
practical test sample is given, and the feasibility of measurement method is proved.
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In this paper, we propose a multi-object tracking method. It uses the object chain from different cameras. Firstly,
according to the Kalman filter, the object region in the next frame could be predicted, and if the overlap area between the
predicted region and the detected region is larger than the threshold, setting the value to 1 in the matching matrix,
otherwise setting the value to 0. Secondly, it will separately update the state of the previous and current frame by line
and column scanning the matching matrix. The same object state should be put into a chain, at the same time, the
relevant frame number and position is noted. Finally, it will realize multi-target tracking by the matched feature in the
object chain from different videos. The experimental results reveal that the proposed method could track the occluded
targets better and reduce greatly the tracking time.
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Image quality assessment (IQA) is a critical issue in image processing applications, but commonly used criterions for
image quality assessment do not map well with perceived quality. The recently proposed structural similarity (SSIM) is
regarded as an excellent work in image quality assessment criterions, but it only consider local information and ignore
some important global concepts. Based on the SSIM image quality assessment criterion and the detection of visual
saliency in image, this paper proposes a learning based saliency weighted structural similarity IQA criterion. The
algorithm combines the SSIM index and saliency map in a machine learning framework to learn a mapping from these
features to perceived image quality. Experiments on a standard image quality assessment database show that our
algorithm performs better than commonly used criterions, and our algorithm captures results which correlate well with
subjective judgments of image quality.
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Large-aperture optical element is widely used in optical engineering and reasonable mounting results in higher
performance. In order to reduce the gravitational sag induced by its own weight, three types of mounting configurations
were proposed and simulated by finite element method, and the effects of axial loads and non-uniformity and asymmetry
were analyzed in the same time. The results showed that full periphery mounting configuration was the optimal
mounting configuration and the optimal axial load was 0.085MPa with the corresponding maximum distortion was
2.32μm, and the effects of non-uniformity and asymmetry on distortion were small.
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This paper presents a selection of image processing methods and algorithms, which are needed to enable the reliable
automation of robotic tasks at the micro and nanoscale. Application examples are automatic assembly of new nanoscale
electronic elements or automatic testing of material properties. Due to the very small object dimensions targeted here, the
scanning electron microscope is the appropriate image sensor. The methods described in this paper can be categorized
into procedures of object recognition and object tracking. Object recognition deals with the problem of finding and
labeling nanoscale objects in an image scene, whereas tracking is the process of continuously following the movement of
a specific object. Both methods carried out subsequently enable fully automated robotic tasks at the micro- and
nanoscale. A selection of algorithms is demonstrated and found suitable.
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We present an image registration method based on geometric pattern matching. The method is applicable to the situation
that there is a similarity transformation between two images. First of all, the edges of the images were detected and the
edge points were described with subpixel position and direction of gradient vector of intensities. The geometric denoising
method was proposed to smooth the position and direction of the edge points. And then a coarse registration was
performed to compute the similarity transformation parameters with pixel accuracy. In the end, a high accuracy
registration based on iterative closest point (ICP) algorithm is used to obtain the final result.
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This paper presents an effective and accurate approach to extract coastlines from InSAR coherence map. The key
technique is to automated extract the island coastline quickly in investigating the changes of the island coastlines using
remote sensing technique. According to the tremendous difference of backscatter in InSAR coherence map between in
sea region and in land region, an automated extracting method based on InSAR coherence map is proposed in this paper.
Firstly, it generates the interferogram and coherence map based on InSAR technique and SAR complex data. Then it gets
the information of coastlines through threshold segmentation and edge detection for the coherence map. At last, we
choose the ERS-1/2 SAR data to carry out the coastline extraction test. The test proves that it is an effective and accurate
approach to extract coastlines from InSAR coherence map.
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In this paper, an approach is proposed for segmentation of multiple contour sequences and recognition of entities for
vision measurement of small precision parts. The approach includes several steps as follows. All contour sequences of
the part are detected at the first place. Secondly, a circle identification method is used to find circular contours in contour
sequences. The identified circular contours are further fitted as individual circles. Then, curvature method is selected to
detect dominant points in the rest contours and height projection method is adopted to classify them as line or arc entities.
In the end, the least-squares method is used to merge and add dominant points. Experimental results show lines, arcs and
circles can be recognized satisfactorily by using the approach presented.
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The optical quality for some special human eyes was evaluated from wavefront aberration data. Wavefront aberrations
were measured by a ray-tracing wavefront aberrometer. The optical quality was estimated by means of objective and
quantitative optical quality metrics of human eyes. The results show that the point spread function patterns and the
values of six optical quality metrics vary with the individual eyes or the levels of aberration. The values of PFWc, SRX,
AreaMTF and SRMTF increase, as well as the values of RMSs and SM decrease, with the more corrected aberration
orders. The great increase of higher-order aberration may be attributed to the pathological changes or refractive surgery,
which results in the distinct degeneration of optical quality of human eye.
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This paper presents an algorithm for generation of a force field from point cloud in three-dimensional space. The force
field is calculated based on the approach of gradient vector flow (GVF). Therefore, the force field is named as 3D GVF
field. By converting the point cloud into a 3D edge image, the algorithm diffuses the gradient of 3D edge image along
the gradient direction of 3D edge image. The generated 3D GVF field of point cloud can be further used for point cloud
processing such as segmentation, reparation or recognition.
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This study aims to further the image mosaic technology, which helps to assemble the images obtained from a digital
camera and eventually obtain a layout image of the lining surface. With the extensive use of mathematical correlations
for distortions produced due to perspective, the errors and use of other machines has significantly reduced. The layout of
the lining surface obtained from successive mosaic of partially overlapping images, which are represented as 2D
orthographic-like and are rectified to form the 3D tunnel-lining surface. A test was carried out in the experimental tunnel
to validate the proposed method and to examine its practicability. The anomalies on the tunnel-lining surface are usually
cracks or a water leakage at any point, neither of which were identifiable through edge detection. Through the
application of a slightly modified Frequency Histogram of Connected Elements method, the resultant image successfully
identified the anomalies on the tunnel lining.
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To detect driver fatigue states effectively and in real time, a driver fatigue detection system was built, which take
ICETEK-DM6347 module as system core, near-infrared LED as light source, and CCD camera as picture gathering
device. An improved PER-NORFACE detection method combined several simple and efficient image processing
algorithms was proposed, which based on principle of PERCLOS method and take the human face location as the main
detection target. To ensure the ability of real-time processing, the algorithms on the DM6437 DaVinci processor were
optimized. Experiments show that the system could complete the driver fatigue states detection accurately and in real
time.
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Large-scale lightweight silicon carbide (SiC) mirrors were manufactured for space. Sintered SiC (SSiC) ceramic was
adopted as the material to manufacture these mirrors. Complex structure designed for highly weight reduction and
installation requirements was near-net-shape formed on SiC green body by digital machining technique before the high
temperature sintering process. The dimensional accuracy of thin ribs and faceplate can be precisely controlled above
99.5%. During sintering process, the temperature distribution was kept uniform enough to avoid residual stress and
deformation in the whole furnace. Isotropic shrinkage occurs during densification from SiC green body to ceramic with a
fluctuation less than 0.3%, which is the dimension error of the final size as well. Mirror surface with low surface
roughness, high shape accuracy and reflectivity was finished by polishing and plating. Moreover, large-scale lightweight
SSiC mirror was demonstrated to be suitable for space use by tests simulating launch conditions and space environments.
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We have observed the formation of photorefractive spatial quasi-stead-state solitons in SBN:75 crystal by electric field
with white beam as background and signal beam intensity of μW magnitude. It was found that the electric field had
obvious effect on the characteristics of laser beam propagation in crystal. It showed a performance of self-focusing that
the output beam from the crystal is proportional to the voltage of the external electric field along the c-axis of the crystal.
At the voltage of 900V(1800V/cm), (2+1) -dimensional bright spatial solitons formed. While applied voltage along the
reverse of c-axis, the diffraction of spot on the output face of the crystal appeared obviously as a performance of
self-defocusing.
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In this paper, the fractionally damped van der pol equation was studied. Firstly, the fractionally damped van der pol
equation was transformed into a set of integer order equations. Then the Lyapunov exponents diagram was given.
Secondly, it was transformed into a set of fractional integral equations and solved by a predictor-corrector method. The
time domain diagrams and phase trajectory were used to describe the dynamic behavior. Finally, the fractionally damped
van der pol equation was used to detect a weak signal.
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Inspired by the recent rapid progress of l1-norm minimization techniques and the great success of sparse dictionary
learning in image modeling, this paper proposes a sparse multi-way models clustering fusion technique to improve the
classification performance in hyperspectral imagery. Multi-way models consider hyperspectral imagery data as a whole
entity to treat jointly spatial and spectral modes. The whole clustering fusion method is composed three steps. Firstly, the
complete hyperspectral data is grouped into several independent sub-band data sources. Then, sparse multi-way model is
used to feature extraction in every band set, and divide the scene into a series of homomorphic regions. At last, we
propose a fusion method to combine the information provided by each band set, it can acquire approximate supervised
classification performance (such as K-nearest Neighbor classifier).The experimental results on the HYDICE imagery
demonstrate the efficiency and superiority of the proposed clustering method to the classical K-means clustering method.
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The 3D reconstruction for freehand 3D ultrasound is a challenging issue because the recorded B-scans are not only
sparse, but also non-parallel (actually they may intersect each other). Conventional volume reconstruction methods can't
reconstruct sparse data efficiently while not introducing geometrical artifacts, and conventional surface reconstruction
methods can't reconstruct surfaces from contours that are arbitrarily oriented in 3D space. We developed a new surface
reconstruction method for freehand 3D ultrasound. It is based on variational implicit function which is presented by Greg
Turk for shape transformation. In the new method, we first constructed on- & off-surface constraints from the segmented
contours of all recorded B-scans, then used a variational interpolation technique to get a single implicit function in 3D.
Finally, the implicit function was evaluated to extract the zero-valued surface as reconstruction result. Two experiment
was conducted to assess our variational surface reconstruction method, and the experiment results have shown that the
new method is capable of reconstructing surface smoothly from sparse contours which can be arbitrarily oriented in 3D
space.
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Near-infrared (NIR) imaging systems simultaneously record spectral and spatial information. Near-infrared imaging
was applied to the identification of imidacloprid in both artificially mixed samples and commercial formulation in this
study. The distributions of technical imidacloprid and additive in the heterogeneous counterfeit were obtained by the
relationship imaging (RI) mode. Furthermore a series of samples which consisted of different contents of uniformly
distributed imidacloprid were prepared and three data cubes were generated at each content. Extracted spectra from those
images were imported to establish the partial least squares model. The model's results were: R2 99.21%, RMSEC 0.0306,
RMSECV 0.0183, RMSECV/mean value 0.0348 and RSEP 0.0784. The prediction relative error of commercial
formulation is 0.0680, indicating the predicted value was correlated to the real content. Lastly the chemical value
reconstruction image of imidacloprid formulation products was calculated by MATLAB program. NIR microscopy
imaging manifests herein its potential in qualitatively identifying the active component in counterfeit pesticide and
quantifying the active component in scanned image.
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By comparing the advantages and disadvantages of two interactive image segmentation algorithms: level set and live
wire, we propose a improved multi-step realization method of interactive image segmentation, which could help the
operators to extract the important anatomical structure features from the femur digital radiographs (DR) images more
accurately. Firstly, a preprocessing step including median filtering and image enhancement was made to eliminate the
noise during the DR imaging; Secondly, with the advantages of level set such as simple operation and fast convergence
rate, the coarse outline contour extraction was realized; Finally, with the advantages of live-wire such as repeated local
operation and high precision, the fine contour extraction of special anatomic areas, the profile of fracture edge and the
overlapping area was realized. So, all the interesting anatomical structure features of DR images were obtained. In this
paper, our method was applied to the complete femur DR images and artificial fracture femur DR images. The
segmentation result shows that our method has a good performance in accuracy and efficiency.
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This paper addresses the problem of describing the primitive structure and the repeating pattern in
texture images. Effective methods exist for statistical analysis for texture recognition and segmentation.
However, the statistical descriptions can hardly reveal the information on the structure of primitives
and how they repeat in the texture image. A method for extracting structure features of texture image is
proposed in this paper: based on an analysis of edge features in scale space, the location and orientation
of edges have been extracted. At coarse scale, edges from the contour of the same primitive are
determined to be linked together by a criteria defined as linking strength, thus the localization of each
primitive is determined. With the corresponding edges at fine scale, the parameterization of primitive
configuration is optimized with parameter space determined repeating patterns as constraints.
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There are a kind of non-linear filters in the active detection problem solution which can weaken the bigger and
strengthen the smaller samples, that can be called as Gaussianization, and to improve performance of subsequent
correlation test. An explicit definition about this kind of nonlinear Gaussianization filter is given at first. In succession,
the two typical nonlinear filters are proposed and studied. One is U-filter, based on the probability density function and
its derivate. The other is G-filter, based on the cumulative distribution function and its inverse. Instances with lake trial
data are illustrated to test these two methods' performance.
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Principal component analysis (PCA) is the common method of compressing data for extracting sample statistical feature
under the condition of meeting the optimal standard deviation. In this paper, it is to improve the recognition speed that the
PCA was used to extract the image features of the chip resistors surface defects when the image is as much as possible to
compress image data under the condition of retain the image defect information as much as possible. The result shows that
PCA can greatly compress the images data during recognizing the chip resistor defect and improve the recognition
accuracy, recognition rate is improved by increasing the training samples under the condition of not affect the recognition
time, and the number of principal components has a suitable value. The defect recognition rate is the best when the main
component number is the 78.57% of the eigenvectors of the training set covariance matrix.
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Super low altitude remote sensing satellite maintains lower flight altitude by means of ion propulsion to improve
resolution and positioning accuracy of imaging images. The design of engineering data for achieving image positioning
accuracy is discussed in this paper based on principles of photogrammetry theory. The line-of-sight exact rebuilding of
each detection element and this direction intersects with the earth's elliptical precisely are ensured by the joint design of
key parameters when the camera on satellite is imaging. These parameters include orbit determination accuracy, attitude
determination accuracy, exposure time of camera, synchronizing time of getting ephemeris and attitude data accuracy,
geometric calibration and checking precise on orbit. Simulation calculation of precision proves that image positioning
accuracy of super low altitude remote sensing satellites is not improved obviously. Attitude determination error of
satellite still restricts positioning accuracy.
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To study the different texture analysis methods on the identification degree of different material,
now make four types of material experiments, through the recognition accuracy of a variety of
materials, to determine the best material texture analysis method. First, list arithmetic, get the GLCM
features, Haralick features, Gabor wavelet features and wavelet energy features, each texture
analysis methods gets four texture parameters of fabrics, fur, wood and stone, design templet;
Secondly, using the Euclidean distance and the Chebychev distance of distance classifier to make
accuracy identification of the above characteristics, in order to determine the different texture
analysis method on the identification degree of different materials.
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