Dr. Stephen R. Delwiche Profile

Dr. Stephen R. Delwiche

at Agricultural Research Service

SPIE Involvement:

Author

Proceedings Article | 17 May 2013 Paper

Inspection of fecal contamination on strawberries using fluorescence imaging

Yung-Kun Chuang, Chun-Chieh Yang, Moon Kim, Stephen Delwiche, Y. Martin Lo, Suming Chen, Diane Chan

Proceedings Volume 8881, 88810G (2013) https://doi.org/10.1117/12.2030715

KEYWORDS: Contamination, Luminescence, Inspection, Safety, Line scan image sensors, Agriculture, Pathogens, Hyperspectral imaging, Imaging systems, Image acquisition

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Proceedings Article | 5 May 2012 Paper

Integration of independent component analysis with near infrared spectroscopy for evaluation of rice freshness

Yung-Kun Chuang, Suming Chen, Stephen Delwiche, Y. Martin Lo, Chao-Yin Tsai, I-Chang Yang, Yi-Ping Hu

Proceedings Volume 8369, 83690X (2012) https://doi.org/10.1117/12.921309

KEYWORDS: Independent component analysis, Calibration, Near infrared, Near infrared spectroscopy, Chemical analysis, Agriculture, Spectroscopy, Nondestructive evaluation, Spectral calibration, Inspection

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Proceedings Article | 5 May 2012 Paper

Development of a single-channel, three-view imaging system with classification model for defect and damage assessment of freefalling cereal grains

I-Chang Yang, Stephen Delwiche, Y. Martin Lo

Proceedings Volume 8369, 83690E (2012) https://doi.org/10.1117/12.921419

KEYWORDS: Imaging systems, Inspection, Cameras, Image classification, Image processing, Feature extraction, Mirrors, Classification systems, MATLAB, Affine motion model

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Currently, inspection of wheat in the United States for grade and class is performed by human visual analysis. This is a time consuming operation typically taking several minutes for each sample. Digital imaging research has addressed this issue over the past two decades, with success in recognition of differing wheat classes, and distinguishing wheat from non-wheat species. Detection of wheat kernel defects, either by damage or disease, has been a greater challenge. A study has been undertaken that uses high-speed black and white imaging at 10-bit photometric resolution to detect damaged kernels one kernel at a time. The system, composed of hardware (camera, lighting, power supplies, and data acquisition card), software (LabVIEW and MATLAB), and analytical (MATLAB and SAS) components, is designed to a) capture images of free-falling kernels at opposing angles through the use of optical grade mirrors, b) parameterize the images and, c) perform classification. The system operates with a 1/30,000 second exposure time though with restrictions on image transfer rate (60 Hz) and image processing routines for feature extraction (currently conducted offline). Fifty samples of hard red and white wheat subjected to weather related damage during plant development were used in this study. Parametric (linear discriminant analysis) and non-parametric (k-nearest neighbor) classification models were tested to determine the image features that best foster recognition of the damage conditions of mold, sprout, and black tip. The morphological features used in classification included area, projected volume, perimeter, elliptical eccentricity, and major and minor axis lengths. Textural features from calculated gray level co-occurrence matrices (including contrast, correlation, energy, and homogeneity), are also under consideration though not reported herein. So far, our results indicate that with as few as three image parameters, classification (damaged vs. sound) levels approach 85 to 90 percent accuracy. Information learned from this study is intended to lead to the streamlining of feature extraction in image-based high speed sorting.

Proceedings Article | 3 June 2011 Paper

Infrared imaging technology for detection of bruising damages of 'Shingo' pear

Byoung-Kwan Cho, Moon Kim, Hoonsoo Lee, Stephen Delwiche

Proceedings Volume 8027, 80270I (2011) https://doi.org/10.1117/12.884564

KEYWORDS: Hyperspectral imaging, Reflectivity, Near infrared, Imaging systems, Image processing, Imaging spectroscopy, Agriculture, Oxides, Skin, Image analysis

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Proceedings Article | 3 June 2011 Paper

Hyperspectral near-infrared reflectance imaging for detection of defect tomatoes

Hoonsoo Lee, Moon Kim, Danhee Jeong, Kuanglin Chao, Byoung-Kwan Cho, Stephen Delwiche

Proceedings Volume 8027, 80270J (2011) https://doi.org/10.1117/12.888098

KEYWORDS: Hyperspectral imaging, Image processing, Binary data, Principal component analysis, Reflectivity, Defect detection, Image classification, Calibration, Agriculture, Imaging systems

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Proceedings Article | 21 April 2010 Paper

Damage and quality assessment in wheat by NIR hyperspectral imaging

Stephen Delwiche, Moon Kim, Yanhong Dong

Proceedings Volume 7676, 767607 (2010) https://doi.org/10.1117/12.851150

KEYWORDS: Visualization, Hyperspectral imaging, Cameras, Imaging systems, Reflectivity, Statistical analysis, Inspection, Near infrared, Safety, Head

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Proceedings Article | 28 April 2009 Paper

Hyperspectral imaging for detection of black tip damage in wheat kernels

Stephen Delwiche, I-Chang Yang, Moon Kim

Proceedings Volume 7315, 73150K (2009) https://doi.org/10.1117/12.818791

KEYWORDS: Hyperspectral imaging, Luminescence, Image processing, Inspection, Reflectivity, Electron multiplying charge coupled devices, Image classification, Imaging systems, Software development, Cameras

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SPIE Journal Paper | 1 February 2009

Enhancement of Fusarium head blight detection in free-falling wheat kernels using a bichromatic pulsed LED design

I-Chang Yang, Stephen Delwiche, Suming Chen, Y. Martin Lo

OE, Vol. 48, Issue 02, 023602, (February 2009) https://doi.org/10.1117/12.10.1117/1.3081092

KEYWORDS: Light emitting diodes, Head, Inspection, Optical engineering, Green light emitting diodes, Reflectivity, Analytical research, Sensors, Optical fibers, Visualization

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Proceedings Article | 26 September 2007 Paper

Optical characterization of free-falling mold-damaged wheat kernels

Stephen Delwiche

Proceedings Volume 6761, 67610G (2007) https://doi.org/10.1117/12.735662

KEYWORDS: Reflectivity, Spectroscopy, Diodes, Head, Inspection, Visible radiation, Sensors, Near infrared, Silicon, Convolution

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Proceedings Article | 23 October 2006 Paper

Improvements in optical sorting of mold-damaged wheat

Stephen Delwiche

Proceedings Volume 6381, 63810A (2006) https://doi.org/10.1117/12.686027

KEYWORDS: Sensors, Analytical research, Spectrometers, Spectroscopy, Interference filters, Optical sorting, Head, Diodes, Nonlinear filtering, Optical testing

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Proceedings Article | 29 December 2000 Paper

Hyperspectral imaging for detection of scab in wheat

Stephen Delwiche, Moon Kim

Proceedings Volume 4203, (2000) https://doi.org/10.1117/12.411752

KEYWORDS: Inspection, Reflectivity, Hyperspectral imaging, Machine vision, Imaging systems, Spatial resolution, Statistical analysis, Visualization, Head, Image analysis

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SPIE Journal Paper | 1 October 1995

Neural network classification of wheat using single kernel near-infrared transmittance spectra

Huaipu Song, Stephen Delwiche, Yud-Ren Chen

OE, Vol. 34, Issue 10, (October 1995) https://doi.org/10.1117/12.10.1117/12.210745

KEYWORDS: Calibration, Neural networks, Transmittance, Near infrared, Data modeling, Proteins, Inspection, Library classification systems, Statistical modeling, Nondestructive evaluation

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Proceedings Article | 6 January 1995 Paper

Noninvasive measurement of moisture distribution in individual wheat kernels by magnetic resonance imaging

Huaipu Song, Stephen Delwiche, Michael Line

Proceedings Volume 2345, (1995) https://doi.org/10.1117/12.198862

KEYWORDS: Magnetic resonance imaging, 3D image processing, Signal to noise ratio, Nondestructive evaluation, 3D metrology, Spatial resolution, Proteins, Computer programming, Fourier transforms, Spectroscopy

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Proceedings Article | 6 January 1995 Paper

High-performance spectrophotometer

David Massie, Stephen Delwiche

Proceedings Volume 2345, (1995) https://doi.org/10.1117/12.198892

KEYWORDS: Spectrophotometry, Computer programming, Computing systems, Agriculture, Control systems, Optical encoders, Ultraviolet radiation, Human-machine interfaces, Analog electronics, Sensors

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Proceedings Article | 12 May 1993 Paper

Determination of wheat kernel hardness by optical measurements

Stephen Delwiche

Proceedings Volume 1836, (1993) https://doi.org/10.1117/12.144045

KEYWORDS: Agriculture, Transmittance, Calibration, Performance modeling, Forestry, Optical testing, Proteins, Inspection, Reflectivity, Humidity

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Showing 5 of 15 publications

Conference Committee Involvement (19)

Sensing for Agriculture and Food Quality and Safety XIV

5 April 2022 | Orlando, Florida, United States

Sensing for Agriculture and Food Quality and Safety XIII

12 April 2021 | Online Only, Florida, United States

Sensing for Agriculture and Food Quality and Safety XII

27 April 2020 | Online Only, California, United States

Sensing for Agriculture and Food Quality and Safety XI

16 April 2019 | Baltimore, MD, United States

Sensing for Agriculture and Food Quality and Safety X

17 April 2018 | Orlando, FL, United States

Sensing for Agriculture and Food Quality and Safety IX

13 April 2017 | Anaheim, CA, United States

Sensing for Agriculture and Food Quality and Safety VIII

20 April 2016 | Baltimore, MD, United States

Sensing for Agriculture and Food Quality and Safety VII

21 April 2015 | Baltimore, MD, United States

Sensing for Agriculture and Food Quality and Safety VI

6 May 2014 | Baltimore, MD, United States

Sensing for Agriculture and Food Quality and Safety V

30 April 2013 | Baltimore, Maryland, United States

Sensing for Agriculture and Food Quality and Safety IV

24 April 2012 | Baltimore, Maryland, United States

Sensing for Agriculture and Food Quality and Safety III

26 April 2011 | Orlando, Florida, United States

Sensing for Agriculture and Food Quality and Safety II

6 April 2010 | Orlando, Florida, United States

Sensing for Agriculture and Food Quality and Safety

14 April 2009 | Orlando, Florida, United States

Special Sessions on Food Safety, Visual Analytics, Resource Restricted Embedded and Sensor Networks, and 3D Imaging and Display

17 March 2008 | Orlando, Florida, United States

Optics for Natural Resources, Agriculture, and Foods II

10 September 2007 | Boston, MA, United States

Optics for Natural Resources, Agriculture, and Foods

3 October 2006 | Boston, Massachusetts, United States

Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality

23 October 2005 | Boston, MA, United States

Nondestructive Sensing for Food Safety, Quality, and Natural Resources

26 October 2004 | Philadelphia, Pennsylvania, United States

Showing 5 of 19 Conference Committees

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