Dictionary size reduction for a faster object recognition in digital holography

Corinne Fournier (1) , Loïc Denis (1) , Mozhdeh Seifi (1) , Thierry Fournel (2)

1 LHC - Laboratoire Hubert Curien [Saint Etienne]
2 Laboratoire Hubert Curien / Eris

Pattern matching methods can be used in the context of digital holography to perform the task of object recognition, classification and position extraction directly from the hologram and not from the reconstructed optical field. These approaches exploit the differences between the objects' holographic signatures caused by class and depth position of the objects. In this talk we will show that such inter-signature variabilities can be captured efficiently in a lower-dimensional vector space using dimensionality reduction methods.

Domains: Computer Science [cs]; Image Processing [eess.IV]

Corinne Fournier, Loïc Denis, Mozhdeh Seifi, Thierry Fournel. Dictionary size reduction for a faster object recognition in digital holography. 12th Workshop on Information Optics, Jul 2013, Puerto de La Cruz, Spain. ⟨ujm-00863131⟩