A classification of emotion and gender using approximation image Gabor local binary pattern

Gender classification and emotion detection plays an important role in the areas security. Gender classification and emotion detection aids in identification of a person by recognizing its gender (male/female) with their emotions (happy/sad) from the face image only. Individual works has been done in the Gender classification and emotion detection fields but not together. In this paper, we proposed a system to do detection of emotion and gender simultaneously for a specific face image. In this paper AIGLBP (Approximation image Gabor local binary pattern) is applied for feature extraction and SVM is used for classification. The number of experiments is initiated on a standard face image databases taken in controlled (FERET and INDIAN FACE) environment. The experimental results demonstrate that the proposed system is effective enough to give high performance in terms of speed and accuracy.

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