基于简化脉冲耦合神经网络的噪声人脸识别

Noise face recognition based on Simplified Pulse Coupled Neural Network

利用简化脉冲耦合神经网络(S-PCNN),提出一种处理椒盐噪声污染的人脸识别新方法.首先采用S-PCNN的相似群神经元同步发放脉冲特性对原图像进行噪声检测,然后结合数学形态学实现对噪声点的消除,最后使用S-PCNN的时间序列(OTS)和欧氏距离进行人脸识别.通过计算机仿真实验表明所提算法是有效的.

A face recognition method for dealing with salt and pepper noise pollution using Simplified Pulse Coupled Neural Network （S-PCNN） was proposed.Firstly the paper uses similar group of S-PCNN neurons issuing synchronous pulses to detect noise of the original image, and then combines with mathematical morphology to achieve elimination noise point,finally adopts the oscillation time sequences （OTS） of S-PCNN and Euclidean distance to process face recognition.Computer simulation results show that the proposed algorithm is effective.