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http://dx.doi.org/10.5391/JKIIS.2007.17.4.511

An Efficient Face Recognition by Using Centroid Shift and Mutual Information Estimation  

Cho, Yong-Hyun (School of Computer and Informantion Comm. Eng., Catholic Univ. of Daegu)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.17, no.4, 2007 , pp. 511-518 More about this Journal
Abstract
This paper presents an efficient face recognition method by using both centroid shift and mutual information estimation of images. The centroid shift is to move an image to center coordinate calculated by first moment, which is applied to improve the recognition performance by excluding the needless backgrounds in face image. The mutual information which is a measurements of correlations, is applied to efficiently measure the similarity between images. Adaptive partition mutual information(AP-MI) estimation is especially applied to find an accurate dependence information by equally partitioning the samples of input image for calculating the probability density function(PDF). The proposed method has been applied to the problem for recognizing the 48 face images(12 persons * 4 scenes) of 64*64 pixels. The experimental results show that the proposed method has a superior recognition performances(speed, rate) than a conventional method without centroid shift. The proposed method has also robust performance to changes of facial expression, position, and angle, etc. respectively.
Keywords
Centroid Shift; First Moment; Adaptive Partition; Mutual Information Estimation; Face Recognition;
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