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Multi-Feature Based Face Recognition Using Histogram Processed

Sompong Valuvanathorn, Supot Nitsuwat


Identification and authentication by face recognition mainly use global face features. However, the recognition performance is not good. This research aims to develop a method to increase the efficiency of recognition using global-face feature and local-face feature with 4 parts: the left-eye, right-eye, nose and mouth. This method is based on geometrical techniques used to find location of eyes, nose and mouth from the frontal face image. We used 110 face images for learning and testing. The histogram processed face recognition technique is used. The results show that the recognition percentage is 89.09%.


Identification and Authentication; Face Recognition; Facial Feature Extraction; Geometric face model; Histogram processed.

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