Abstract
Facerecognition ismainlyused in biometric applications, surveillance systems and computer vision.Themajorproblem while recognizingfacesarisesdue topose variations, background illumination invariants and facial expressions.Theproposed two-stage classifier aims to recognize given inputfaceimages usingk-NNand SVM. The use of two separate classifiers, one after the other, improves the system recognition accuracy.The pre processed face images are then utilized toextractprominent features by Histogram of Oriented Gradients (HOG).In the initial stage, k-NN classifier was used and afterwards, unrecognized face images were tested with SVM classifier.It is found that recognition accuracy increased by cascading k-NN followed bySVM.The two-stage classifierachieved a recognition accuracy of 95.2%.
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