Journal Paper

Paper Title - Gender Classification From Face Images With Local Texture Pattern


Abstract
Recognizing human gender automatically by a computer is a challenging problem. It has been attracting research attention due to its wide real-life applications. Gender classification can be viewed as an essential preprocessing step in face recognition. Because human faces contain a lot of really useful information, many approaches based on facial features have been investigated for gender classification. In this paper, we present a novel texture pattern as feature descriptor to identify the gender from the facial images. The classification is performed by using a support vector machine. Experimental results on the FERET database are provided to illustrate the proposed approach is an effective method, compared to other similar methods. Keywords- Gender Classification, Local Texture Pattern, Support Vector Machine


Author - Yi‐Jui Li, Chih‐Chin Lai, Chih‐Hung Wu, Shing‐Tai Pan, Shie‐Jue Lee

Citation - Yi‐Jui Li   ,   Chih‐Chin Lai   ,   Chih‐Hung Wu   ,   Shing‐Tai Pan   ,   Shie‐Jue Lee   ,   Yi‐Jui Li, Chih‐Chin Lai, Chih‐Hung Wu, Shing‐Tai Pan, Shie‐Jue Lee " Gender Classification From Face Images With Local Texture Pattern " , International Journal of Industrial Electronics and Electrical Engineering , Volume-3,Issue-11  ( Nov, 2015 )

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| Published on 2015-12-01