Abstract
Variations in lighting conditions make face recognition an even more challenging and difficult task. In this paper, a novel approach is proposed to handle the illumination problem. Our method can restore a face image captured under arbitrary lighting conditions to one with frontal illumination by using a ratio-image and an iterative algorithm. The restored images with frontal illumination are used for face recognition by means of PCA. Experimental results demonstrate that our method can achieve a higher recognition rate, based on the Yale B and Yale database. Moreover, our algorithm has several advantages over other previous algorithms: (1) it does not need to estimate the face surface normals and the light source directions; (2) it does not need many images captured under different lighting conditions for each person, nor a set of bootstrap images that includes many images with different illuminations; and (3) it does not need to detect accurate positions of some facial feature points and to warp the image for alignment, etc.
Original language | English |
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Title of host publication | [Missing Source Name from PIRA] |
Pages | 105-108 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 2004 |
Event | International Symposium on Intelligent Multimedia, Video and Speech Processing [ISIMP] - Duration: 1 Jan 2004 → … |
Conference
Conference | International Symposium on Intelligent Multimedia, Video and Speech Processing [ISIMP] |
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Period | 1/01/04 → … |
Keywords
- Edge detection
- Face recognition
- Image segmentation
- Iterative methods
- Lighting
- Principal component analysis