【摘要】 针对K近邻和支持向量机人脸识别率较低的问题,采用一种KNN和SVM融合的识别方法。提出了一种Gabor小波和主成分分析进行人脸特征提取,KNN-SVM进行分类的人脸识别方法。基于ORL和YALE人脸库中进行实验,结果表明该算法较KNN和SVM中任何一个的识别率都要高,且识别率最高可达到98.89%。更多还原

【Abstract】 In view of the poor face recognition rate of the K Nearest neighbor and support vector machine( SVM),a KNN and SVM fusion recognition method is proposed with a Gabor wavelet and principal component analysis( PCA) for face feature extraction and KNN-SVM classification method for face recognition. Experiments based on ORL and YALE face database show that the proposed algorithm offers a recognition rate up to 98. 89%,higher than both KNN and SVM.更多还原