Author_Institution :
Coll. of Geomatics, Xi´´an Univ. of Sci. & Technol., Xi´´an, China
Abstract :
Face recognition is a front complex subject, which involves Physiology, Psychology, Image Processing, Computer Vision, Pattern Recognition and Mathematics. As a research success in the field of wavelet analysis theory, WNN(Wavelet Neural Network), a feed-forward network, avoids the blindness in structure design of BP(Back propagation) neural network, excludes the probability of sub-optimization in local non-linear optimization problems during network training process and has the capability of function learning and popularization. This paper presents a face recognition algorithm based on wavelet neural network. This algorithm depends on the multi-resolution property of wavelet and the robustness and memorization features of neural network, as well as combines with the wavelet neural network step adjustment algorithm, a wavelet neural network is designed for the use of face recognition. Its effectiveness and accuracy are verified by some experiments.
Keywords :
backpropagation; face recognition; feedforward neural nets; wavelet transforms; BP; WNN; back propagation; computer vision; face recognition method; feedforward network; image processing; pattern recognition; wavelet neural network; Algorithm design and analysis; Artificial neural networks; Convergence; Face; Face recognition; Optimization; Training; WNN (Wavelet Neural Network); feature extraction; image processing; pattern recognition;