Abstract
The feasibility of classification of stochastic images for color vision in real time has been investigated with two approaches. First, a hybrid incoherent optical correlator based on a quasi-monochromatic cathode ray tube (CRT) is sequentially operated on red, green, and blue channels for statistical pattern recognition. Second, a color TV monitor is employed in the incoherent optical correlator to achieve spectral–spatial statistical pattern recognition in parallel in real time. The spectral–spatial statistical pattern recognition filter is designed with the least-squares linear mapping technique and is compensated for the smearing effects due to the finite spectral bandwidth of the light from CRTs. The experimental results provided demonstrate better recognition reliability when the spectral–spatial filters are used than when only spatial filters are employed.
© 1987 Optical Society of America
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