Abstract
Volume holographic associative storage in a photorefractive crystal has some special properties such as multichannal operation, parallel processing, and real-time response. It can provide a suitable mechanism to develop an optical correlation system for image recognition. In this paper, a practical image recognition system based on such mechanism is proposed and constructed. Wavelet packet theory is introduced in this system to solve the cross-talk as the same time to improve the parallelism and the storage capability of the system. Through the wavelet packet bases, a set of eigen-images, which are regarded as the reference images for recognition in the associative correlation, are extracted from the training images. Since wavelet packet transform can decompose information through different orthogonal bases in different depths, and different entropy can be used to evaluate the weight of each basis, the way to select the best analyzing bases which is corresponding to the best eigen-images then can be discussed and achieved. Furthermore, different kinds of wavelet packet and the number of training images also influence the way of selection. Basic theoretical analysis of these factors is presented, and experimental results are given for future research.
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