IEICE Electronics Express
Online ISSN : 1349-2543
Improving predictive accuracy by evolving feature selection for face recognition
Nan LiuHan Wang
Author information

2008 Volume 5 Issue 24 Pages 1061-1066


Face recognition system usually consists of feature extraction and pattern classification. However, not all of extracted facial features contribute to the classification positively because of the variations of illumination and poses in face images. In this paper, an evolutionary feature selection algorithm is proposed in which discrete cosine transform (DCT) and genetic algorithms (GAs) are utilized to create a framework of feature acquisition. In detail, the face images are first transformed to frequency domain through DCT, then GAs are used to seek for optimal features in the redundant DCT coefficients where the generalization performance guides the searching process. Furthermore, an entropy-based extension on proposed evolving feature selection method is presented. In experiments, two face databases are used to evaluate the effectiveness of our proposals.

Information related to the author
© 2008 by The Institute of Electronics, Information and Communication Engineers
Previous article Next article