A Spiking Neural Networks Based Face Recognition Algorithm

Abstract

In this paper, the complexity algorithm is used to locate the human eyes, and then the best threshold method is used to locate the human eyes accurately. This method is more accurate than the gray projection method, and it is faster and less affected by the light and noise. Spiking neural networks, which inherit the parallel mechanism from biological system, are used to extract the face features. The spiking neural networks can remember key features of a visual image through synapse strength distribution and recall the visual image by triggering a specific neuron. Based on the key features, the nearest neighbor classifier is used for matching faces. Experimental results show that the proposed algorithm of eye location works well and has advantages about eye location in multi-position and complex background, and the face features extraction based on spiking neural networks can achieve high recognition rate and reduce the time. Furthermore, the algorithm can be transformed to GPU platform and can be speed up dramatically.