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Journal Articles Journal of the Optical Society of America. A Optics, Image Science, and Vision Year : 2013

Fast and accurate 3D object recognition directly from digital holograms

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Mozhdeh Seifi
  • Function : Author
  • PersonId : 763147
  • IdRef : 178790753
Loic Denis
Corinne Fournier

Abstract

Pattern recognition methods can be used in the context of digital holography to perform the task of object detection, classification, and position extraction directly from the hologram rather than from the reconstructed optical field. These approaches may exploit the differences between the holographic signatures of objects coming from distinct object classes and/or different depth positions. Direct matching of diffraction patterns, however, becomes computationally intractable with increasing variability of objects due to the very high dimensionality of the dictionary of all reference diffraction patterns. We show that most of the diffraction pattern variability can be captured in a lower dimensional space. Good performance for object recognition and localization is demonstrated at a reduced computational cost using a low-dimensional dictionary. The principle of the method is illustrated on a digit recognition problem and on a video of experimental holograms of particles.
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Dates and versions

ujm-00985394 , version 1 (02-05-2014)
ujm-00985394 , version 2 (21-05-2014)

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Mozhdeh Seifi, Loic Denis, Corinne Fournier. Fast and accurate 3D object recognition directly from digital holograms. Journal of the Optical Society of America. A Optics, Image Science, and Vision, 2013, 30 (11), pp.2216-2224. ⟨10.1364/JOSAA.30.002216⟩. ⟨ujm-00985394v2⟩
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