DocumentCode :
3746469
Title :
Multi-scale Local Binary Pattern histogram for gender classification
Author :
Yanan Xu;Yong Zhao;Yongjun Zhang
Author_Institution :
College of Information Engineering, Shenzhen Graduate School of Peking University, Shenzhen, China
fYear :
2015
Firstpage :
654
Lastpage :
658
Abstract :
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.
Keywords :
"Feature extraction","Support vector machines","Histograms","Data mining","Robustness","Internet","Databases"
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2015 8th International Congress on
Type :
conf
DOI :
10.1109/CISP.2015.7407959
Filename :
7407959
Link To Document :
بازگشت