Multiplexing of volume holographic wavelet correlation processor

Volume holographic associative memory in a photorefractive crystal provides an inherent mechanism to develop a multi-channel correlation identificatio n system with high parallelism. Wavelet transform is introduced to improve discrimination of the system. We first investigate parameters of the system for parallelism enhancement, and then study multiplexing of the system on input objects and wavelet filters. A general volume holographic wavelet cor relation processor has a single input-object channel and a single wavelet-f iltering channel. In other words, it can only process one input object with one wavelet filter at a same time. Based on the fact that a volume hologra phic correlator is not a shift-invariant system, multiplexing of input obje cts is proposed to improve parallelism of the processor. As a result, sever al input objects can be recognized simultaneously. Multiplexing of wavelet filters with different wavelet parameters is also achieved by a Dammann gra ting. Wavelet correlation outputs with different filters are synthesized to improve recognition accuracy of the processor. Corresponding experimental results in human face recognition are given. The combination of the input o bject multiplexing and the wavelet filter multiplexing is also described. ( C) 2000 Elsevier Science B.V. All rights reserved.