Multi-scale Local Binary Pattern Histogram for Gender Classification

被引:0
|
作者
Xu, Yanan [1 ]
Zhao, Yong [1 ]
Zhang, Yongjun [2 ]
机构
[1] Peking Univ, Shenzhen Grad Sch, Coll Informat Engn, Shenzhen, Peoples R China
[2] Guizhou Univ, Coll Comp Sci & Technol, Guiyang, Peoples R China
关键词
Gender Classification; Local Binary Pattern Histogram; DoG (Difference of Gaussian); SVM; SCALE;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
LBP (Local Binary Pattern) is a commonly used operator to extract LBPH (LBP histogram) of an image for local texture description. For gender classification, we proposed an innovative method by extracting multi-scale LBPH in DoG (Difference of Gaussian) space in this paper. Given a facial image, we firstly preprocess it meticulously to avert the local variations of images which probably be caused by expression, pose and so on. And then we extract multi-scale LBPH features in DoG space which can extract richer local and global interested information of the facial image. Gender classification is performed via a standard binary classifier: SVM. We conducted experiment on 2,410 FERET images and 1,100 images of our collected dataset from the Internet. The best performance of 97.7% is achieved, and the method also performs robustly.
引用
收藏
页码:654 / 658
页数:5
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