| 基于GPCA的KNNY与SVM融合的人脸识别方法 |
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| 引用本文： | 焦淑红,孙志帅.基于GPCA的KNNY与SVM融合的人脸识别方法[J].电子科技,2016,29(2):74. |
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| 作者姓名： | 焦淑红 孙志帅 |
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| 作者单位： | (哈尔滨工程大学 信息与通信工程学院,黑龙江 哈尔滨 150001) |
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| 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%。
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| 关 键 词： | K近邻 支持向量机 Gabor小波 PCA 人脸识别 |
Face Recognition Based GPCA of KNN and SVM Fusion |
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| JIAO Shuhong,SUN Zhishuai.Face Recognition Based GPCA of KNN and SVM Fusion[J].Electronic Science and Technology,2016,29(2):74. |
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| Authors: | JIAO Shuhong SUN Zhishuai |
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| Affiliation: | (School of Information and Communications Engineering,Harbin Engineering University,Harbin 150001,China) |
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| 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. |
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| Keywords: | KNN SVM Gabor wavelet PCA face recognition |
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