Simulation study on the performance of several classifiers in face recognition

C. Chen, Jia Tang
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引用次数: 1

Abstract

Classifier is the important content in the face recognition system. This paper uses PCA to extract the face image feature and then compares the recognition performance of several classifiers. Based on ORL and YALE face database, the paper carries out simulation experiment by using minimum distance classifier, nearest-neighbor classifier and K-neighbor classifier respectively. Besides, this paper researches different distance measures' effects on the recognition result of the classifiers, Euclidean distance, Minkowski distance, cosine distance and absolute distance.
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几种分类器在人脸识别中的性能仿真研究
分类器是人脸识别系统的重要内容。本文利用主成分分析法提取人脸图像特征,然后比较几种分类器的识别性能。基于ORL和YALE人脸数据库,分别采用最小距离分类器、最近邻分类器和k近邻分类器进行仿真实验。此外,本文还研究了不同距离度量对分类器识别结果的影响,欧几里得距离、闵可夫斯基距离、余弦距离和绝对距离。
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