Horizontal Features based Illumination Normalization Method for Face Recognition

被引：0
|
作者：
Ibrahim, Muhammad Talal [1 ]
Guan, Ling [1 ]
Niazi, M. Khalid Khan [2 ]
机构：
[1] Ryerson Multimedia Lab, Toronto, ON, Canada
[2] Uppsala Univ, Ctr Image Anal, Uppsala, Sweden
来源：
PROCEEDINGS OF THE 7TH INTERNATIONAL SYMPOSIUM ON IMAGE AND SIGNAL PROCESSING AND ANALYSIS (ISPA 2011) | 2011年
关键词：
TRANSFORM; MODELS;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper presents a novel filtering method for face recognition under varying illumination. The proposed method starts by normalizing the given input image by gamma transformation. The shadow artifacts in the normalized image are reduced with the decimation free directional filter banks (DDFB). We have used correlation coefficient as a similarity measure for face recognition. Empirically, we have proven that most of the discriminating features in a human face are horizontal in nature. The efficiency of the proposed method is evaluated on two public databases: Yale Face Database B, and the Extended Yale Face Database B. Experimental results demonstrate that the proposed method achieves higher recognition rate under varying illumination conditions in comparison with some other existing methods.
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页码：684 / 689
页数：6
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