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30 March 2020 Optical architectures for pattern recognition with the generalized Hough transform
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The generalized Hough transform (GHT) is a well-established technique for the recognition of geometrical fea- tures out of images corrupted by noise, with disconnected boundaries or where the target is partially occluded. As an alternative to the conventional procedure of direct imaging of the scene of interest and mapping to an accumulator or Hough parameter space, we can directly obtain the image transformed under GHT in an incoherently illuminated optical architecture where the pupil is codified according to the target of interest. Parallel processing inherent of optical devices then allows for real-time performance and shift-invariant pattern recognition. Besides, by exploiting the redundancy derived from multiview sensing of the input and its out- of-focus capture with an adequate pupil array, we can obtain in a snapshot the GHT with invariance to target shift, scale, and orientation. Finally, in order to enhance the robustness of the original algorithm in detecting an object out of a single image, we can also consider matching of a pair of corresponding (according to a perspective shift) templates to a given stereo pair of a 3d scene, since the redundancy that results from the simultaneous transformation of both images can overcome the drawbacks (resulting for example from occlusion) that affect the separate matching of an individual template to a given image.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ariel Fernández "Optical architectures for pattern recognition with the generalized Hough transform", Proc. SPIE 11351, Unconventional Optical Imaging II, 1135121 (30 March 2020);

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