Abstract
Volume holographic associative memory in a photorefractive crystal provides an inherent mechanism to develop a multi-channel correlation identification 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 correlation processor has a single input-object channel and a single wavelet-filtering 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 holographic correlator is not a shift-invariant system, multiplexing of input objects is proposed to improve parallelism of the processor. As a result, several input objects can be recognized simultaneously. Multiplexing of wavelet filters with different wavelet parameters is also achieved by a Dammann grating. 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 object multiplexing and the wavelet filter multiplexing is also described.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
