Color component transformations for optical pattern recognition

V. Kober, V. Lashin, I. Moreno, J. Campos, M. J. Yzuel, L. P. Yaroslavsky

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Several elementwise component transformations performed over primary color image components (RGB) before optical multichannel correlations are proposed to improve real-time multispectral pattern recognition. The first transformation is deduced from the theory of the optimal filter for object location and recognition extended to multispectral images. Several modifications of this transformation are studied. We investigate these transformations in terms of noise robustness and discrimination capability. Computer simulation with noisy input images for various kinds of correlation filter are presented to illustrate improvement of color pattern recognition by using the proposed transformations. Experimental results are also presented.

Original languageEnglish
Pages (from-to)2656-2669
Number of pages14
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Issue number10
StatePublished - Oct 1997


Dive into the research topics of 'Color component transformations for optical pattern recognition'. Together they form a unique fingerprint.

Cite this