Title :
Face Recognition Based on Binary Edge Map and Support Vector Machine
Author :
Qiu, Xuena ; Wang, Wei ; Song, Jiatao ; Zhang, Xuejun ; Liu, Shirong
Author_Institution :
Coll. of Electron. & Inf. Eng., Ningbo Univ. of Technol., Ningbo
Abstract :
In this paper, a novel face recognition scheme is presented. Our method uses binary edge map (BEM) as face representation and employs support vector machine (SVM) as face classifiers. The BEM is extracted using locally adaptively threshold (LAT) method. Experimental results show that a face recognition rate of 92.73% can be achieved on 165 Yale face images and 95.62% can be achieved on 798 AR images, indicating that the proposed approach is robust to lighting changes.
Keywords :
face recognition; support vector machines; Yale face images; binary edge map; face recognition; locally adaptively threshold; support vector machine; Data mining; Educational institutions; Face recognition; Independent component analysis; Lighting; Robustness; Spatial databases; Support vector machine classification; Support vector machines; Training data;
Conference_Titel :
Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on
Conference_Location :
Wuhan
Print_ISBN :
1-4244-1120-3
DOI :
10.1109/ICBBE.2007.136
