Pixel selection based on discriminant features with application to face recognition

Authors:
Sang-Il Choi;Chong-Ho Choi;Gu-Min Jeong;Nojun Kwak
Affiliations:
Department of Applied Computer Engineering, Dankook University, 126, Jukjeon-dong, Suji-gu, Yongin-si, Gyeonggi-do 448-701, Republic of Korea;School of Electrical Engineering and Computer Science, Seoul National University, #047, San 56-1, Sillim-dong, Gwanak-gu, Seoul 151-744, Republic of Korea;Electrical Engineering, Kookmin University, 861-1, Jeongeung-dong, Songbuk-gu, Seoul 136-702, Republic of Korea;Division of Electrical and Computer Engineering, Ajou University, San 5, Woncheon-dong, Yeongtong-gu, Suwon 443-749, Republic of Korea
Venue:
Pattern Recognition Letters
Year:
2012

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Abstract

We propose a pixel selection method in a face image based on discriminant features for face recognition. By analyzing the relationship between the pixels in face images and features extracted from them, the pixels that contain a large amount of discriminative information are selected, while the pixels with less discriminative information are discarded. The experimental results obtained with various face databases show that the proposed pixel selection method results in improved recognition performance, especially in the presence of illumination or facial expression variations. Additionally, the proposed method greatly reduces the memory size and computational load in the face recognition process.