Abstract

Face recognition has become an important issue in many applications such as security systems, credit card verification and criminal identification. The recently proposed shape descriptor, Pyramid Histogram of Oriented Gradients (PHOG) features, counts occurrences of gradient orientation in localized portions of an image and has been proved as an efficient tool for providing spatial distribution of edges. In this paper, we proposed to use pyramid histogram of oriented gradients (PHOG) as the features extracted for face recognition. The obtained feature vectors are fed up into Support Vector Machine (SVM) classifier for classification. Experiments carried out on UMIST Face Database databases that both frontal head images and rotated head images are investigated. The experimental results show this approach can be used to automatically identify the faces more effective.

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