SPECTRAL RANGE SELECTION FOR FACE RECOGNITION UNDER VARIOUS ILLUMINATIONS

被引:8
作者
Chang, H. [1 ]
Yao, Y. [1 ]
Koschan, A. [1 ]
Abidi, B. [1 ]
Abidi, M. [1 ]
机构
[1] Univ Tennessee, IRIS Lab, Knoxville, TN 37996 USA
来源
2008 15TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-5 | 2008年
关键词
face recognition; multispectral imaging; Jeffrey divergence; kernel density estimation; IMAGES;
D O I
10.1109/ICIP.2008.4712365
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Multipectral imaging and fusion of multispectral images in visible spectrum have been employed and proved to enhance the recognition performance over conventional broad-band images, especially when the illumination changes. In this paper, we further our study toward the recognition performance of a smaller number of spectral band images. Given the illumination, we propose an automated method that specifies the optimal spectral ranges to achieve an improved recognition performance compared with conventional broad-band images. Our discovery can be practically used for a new customized sensor design associated with given illuminations for an improved face recognition performance over conventional broad-band images.
引用
收藏
页码:2756 / 2759
页数:4
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