Abstract
This paper presents a novel method for solving face gender recognition problem. This method employs 2D Principal Component Analysis, one of the prominent methods for extracting feature vectors, and Support Vector Machine, the most powerful discriminative method for classification. Experiments for the proposed approach have been conducted on FERET data set and the results show that the proposed method could improve the classification rates.
Original language | English |
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Title of host publication | 2010 Fourth International Conference on Network and System Security: NSS 2010 |
Editors | Yang Xiang, Pierangela Samarati, Jiankun Hu, Wanlei Zhou, Ahmad-Reza Sadeghi |
Place of Publication | Piscataway, N.J., USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 579-582 |
Number of pages | 4 |
ISBN (Print) | 9781424484843 |
DOIs | |
Publication status | Published - 2010 |
Event | Fourth International Conference on Network and System Security (NSS 2010), - Melbourne, Australia Duration: 1 Sept 2010 → 3 Sept 2010 |
Conference
Conference | Fourth International Conference on Network and System Security (NSS 2010), |
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Country/Territory | Australia |
City | Melbourne |
Period | 1/09/10 → 3/09/10 |