An optical image recognition system based on the mechanism of volume holographic storage and best wavelet packet basis selection is proposed and constructed. Volume holographic associative storage in a photo-refractive crystal has some special properties, which can provide a suitable mechanism to develop an optical correlation system for image recognition. Wavelet packet theory is introduced in this optical system to reduce the number of images stored in the crystal. Through best wavelet packet basis selection, a set of best eigen-images, which will be stored in the crystal as the reference images for recognition, are extracted from a large number of training images. Correlation output between these eigen-images and input ones can be applied for classification and recognition according to the different light intensities of angularly separated beams. Theoretical analysis and experimental results both show this scheme is practical and can significantly reduce the data stored in the crystal while the accurate rate of recognition is still high.
In this paper, a novel optical correlation system on the basis of wavelet packet theory and the mechanism of volume holographic associative storage is proposed for image recognition. Through the wavelet packet transform, a set of best eigen-images, which are regarded as the reference images for recognition in the associative correlation, are extracted from the training images, and then stored into a volume holographic crystal using the two-wave mixing volume holographic storage technique. When any image for identification is input into the crystal which means a correlator, angularly separated beams with different light intensities are obtained simultaneously. They represent the optical correlation results between the input and the set of eigen-images, and can be applied for the classification and recognition. This process takes the advantages of both the agility of wavelet packet transform and the high degree of parallelism of the photorefractive correlator. Theoretical analysis of this process is presented, and experimental results are given.
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.