Face Recognition Based on Euclidean Distance and Texture Features
Computational and Information Sciences（2013）
摘要
As a kind of statistical features, texture features often have a rotary deformation, and have strong resistibility to noise. The paper first constructs the gray level co-occurrence matrix of face image to describe texture feature of face image, and then uses the classification method of minimum weighted Euclidean distance to fulfill the matching and identification of face. Experiments results have shown that recognition rate was greatly increased by the combination of weighted Euclidean distance and texture feature.
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关键词
minimum weighted euclidean distance,rotary deformation,image matching,face recognition,face image,statistical analysis,euclidean distance,classification method,statistical feature,matrix algebra,face matching,texture features,statistical features,weighted euclidean distance,texture feature,experiments result,gray level co-occurrence matrix,gray level cooccurrence matrix,face identification,image texture,recognition rate,correlation,feature extraction,face,vectors
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