Real-time human face recognition using eigenface based optical filtering

In this paper, we describe a human face recognition system, which is based on an incoherent optical correlator. A liquid crystal display (LCD) panel is used as the real-time spatial,light modulators (SLMs). A set of eigenfaces, which was extracted from 200 training images, is used as image filters in the reference plane of the correlator. Since the face images can be approximated by different linear combinations of a relatively few eigenfaces corresponding to large eigenvalues, they can be efficiently distinguished from one another by a small set of the weight coefficients (a feature vector), which is derived by projecting, the input image onto every selected eigenface. Recognition can be performed by a simple minimum distance decision rule. We use the optical correlator as the feature. extractor and the optical correlation results between the input image and the eigenfaces as the features. By using the optical correlation operation instead of the projection operation, much more features can be got parallelly. By using the eigenfaces as image filters instead of the original images in the training set, the numbers of optical correlation operation, can be greatly reduced compared to the original numbers of the training set.