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一种基于改进弹性束图匹配的人脸识别 被引量:3

An Improved Face Recognition Algorithm Based on Elastic Bunch Graph Matching
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摘要 针对基于弹性束图匹配(EBGM)算法的正面人脸识别,提出了一种新的优化理论。在EBGM算法中,在抽取脸部图像特征之前,需要首先预设好Gabor小波的波长。为了对EBGM算法进行优化,提出了采用遗传算法(GA)对Gabor小波波长进行最佳选择。为了对改进的算法进行评估,实验对300个FERET人脸数据库类进行了测试。在训练阶段,每个类中只取出一幅图像用来训练。经过优化后的EBGM算法匹配运算大幅度减少,识别率大约为90%,运行速度提高至原EBGM算法的1.5倍。 In this paper a new method for optimization of Elastic Bunch Graph Matching (EBGM) algorithm in frontal face recognition is presented.In EBGM algorithm,some predetermined wavelength of Gabor wavelet is used to extract features from face image.For optimization of EBGM algorithm,Genetic Algorithm (GA) is used to select the best wavelengths of Gabor wavelet. For evaluation,algorithm has been tested on 300 classes of FERET face database.In training phase, only one image per class is trained.
出处 《工业控制计算机》 2009年第9期44-46,共3页 Industrial Control Computer
关键词 弹性束图匹配(EBGM) 人脸识别 GABOR小波 遗传算法 Elastic Bunch Graph Matching (EBGM),face recognition,Gabor wavelet,genetic algorithm
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