The multi-sensor, high accuracy, 4 axes gyro-stabilised turret system (LEOSS-T) designed by LEONARDO SPA - Electronics Division for airborne surveillance applications has been transformed in a 3kW Power Laser Effector substituting one of the sensor with the Optical Head of a 3 kW single mode IPG Fiber Laser. Inside the LEONARDO LASER Facility, we demonstrated that the LEOSS Laser Effector system is able to: detect and track a micro drone; determine and maintain the aim point for the time necessary to obtain the desired effect on the target. Drone Dazzling and shooting-down have been tested. Demonstration setup and results are presented.
An optical noninvasive inspection tool is presented to, in vivo, better characterize biological tissues such as human skin.
The method proposed exploits a multispectral imaging device to acquire a set of images in the visible and NIR range.
This kind of information can be very helpful to improve early diagnosis of melanoma, a very aggressive cutaneous
neoplasm, incidence and mortality of which continues to rise worldwide. Currently, noninvasive methods (i.e.
dermoscopy) have improved melanoma detection, but the definitive diagnosis is still achieved only by invasive method
(istopathological observation of the excised lesion). The multispectral system we developed is capable of imaging layers
of structures placed at increasing depth, thanks to the fact that light propagates into the skin and reaches different depths
depending on its wavelength. This allows to image many features which are less or not visible in the clinical and
dermoscopic examination. A new semeiotics is proposed to describe the content of multispectral images. Dermoscopic
criteria can be easily applied to describe each image in the set, however inter-images correlations need new suitable
descriptors. The first group of new parameters describes how the dermoscopic features, vary across the set of images.
More aspects are then introduced. E.g. the longest wavelength where structures can be detected gives an estimate of the
maximum depth reached by the pigmented lesion. While the presence of a bright-to-dark transition between the
wavebands in the violet to blue range, reveals the presence of blue-whitish veil, which is a further malignancy marker.
Maximization of Mutual Information routines proved to be suitable for registration of multimodal images. Here a
method is proposed to select, in a set of candidates, the image which has a closer resemblance with a given external
one. Such algorithm is intended to serve within a wider scope procedure for the automatic texturing of 3D models,
where the initial 2D-3D registration problem is shifted to a 2D-2D registration challenge. In order to improve its
performance a number of variations in the way the Mutual Information is computed are introduced and a method to
judge its reliability is proposed.
Melanoma is a very aggressive cutaneous neoplasm, incidence and mortality of which continues to rise worldwide.
Identification of initial melanoma may be difficult because it may be clinically, and sometimes also dermoscopically,
indistinguishable from benign lesions. Currently definitive diagnosis is made only by histopathological observation of
the excised lesion. Several tools have been developed to help detecting malignant lesions. Dermoscopy highlights
numerous characteristic features of the lesion and of the pigmented network. The method we propose exploits a
multispectral imaging device to acquire a set of images in the visible and NIR range. Thanks to the fact that light propagates into the skin and reaches different depths depending on its wavelength, such a system is capable of imaging
layers of structures placed at increasing depths. Therefore a new semeiotics is proposed to describe the content of such images. Dermoscopic criteria can be easily applied to describe each image in the set, however inter-images correlation needs new suitable descriptors. The first group of new parameters describes how the dermoscopic ones, vary across the set of images. More features are then introduced. E.g. the longest wavelength where structures can be detected gives an
estimate of the maximum depth reached by the pigmented lesion. While the presence of a bright-to-dark transition
between the wavebands in the violet to blue range, reveals the presence of blue-whitish veil, which is a further
malignancy marker.
A new automatic method capable of registering multimodal images like terrain maps and multispectral data is presented.
In order to speed up the processing, given the large amount of data typical of such settings, the method exploits a multi-resolution
approach, which may select different similarity measures in consideration of image resolution and size. In
fact, the performances of Cross Correlation and Maximization of Mutual Information (MMI) on images of different
resolution and size have been evaluated and are described The adaptive strategy adopted is designed to exploit the
strengths and to overcome the limitations of the similarity criteria employed. In case multimodal views are to be
registered on 3D models, MMI is to be preferred. The strategies to improve its performance also on smaller images are
presented.
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