摘要
基于简化脉冲耦合神经网络(S-PCNN),提出了一种新颖的人脸识别方法。首先通过对神经元振荡特性的分析,将神经元振荡时间序列(OTS)分解为捕获性振荡时间序列(C-OTS)和自激性振荡时间序列(S-OTS)。然后通过图像几何变换和振荡频图,分析了X-OTS(OTS、C-OTS和S-OTS)的鉴别特性。最后利用C-OTS+S-OTS和余弦距离测度给出了人脸识别的系统结构。人脸库中的实验结果验证了所提方法的有效性,显示了它比其它传统算法具有更好的识别性能。
A novel face recognition method using Simplified Pulse Coupled Neural Network was proposed. First by the analysis of the oscillation characteristics for neurons, the neuronal Oscillation Time sequences （OTS） were decomposed to captured-OTS（C-OTS） and self-OTS（S-OTS）. Then the identification characteristics for X-OTS（OTS, C-OTS and S-OTS） were analyzed by image geometric transformation and oscillation frequency map. Finally,a face recognition system structure was given with C-OTS＋S-OTS and cosine distance. Experimental results on face database verify the effectiveness of the proposed method, and it shows better recognition performance than other traditional methods.
出处
《计算机科学》
CSCD
北大核心
2014年第2期297-301,共5页
Computer Science
基金
国家自然科学基金(61065008)
云南省应用基础研究计划项目(2012FD003)资助
关键词
简化脉冲耦合神经网络
振荡时间序列
人脸识别
Simplified pulse coupled neural network,Oscillation time sequence,Face recognition
