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This paper proposes a new technique for automatic face recognition usingintegrated peaks of the Hough transformed significant blocks of the binarygradient image. In this approach firstly the gradient of an image is calculatedand a threshold is set to obtain a binary gradient image, which is lesssensitive to noise and illumination changes. Secondly, significant blocks areextracted from the absolute gradient image, to extract pertinent informationwith the idea of dimension reduction. Finally the best fitted Hough peaks areextracted from the Hough transformed significant blocks for efficient facerecognition. Then these Hough peaks are concatenated together, which are usedas feature in classification process. The efficiency of the proposed method isdemonstrated by the experiment on 1100 images from the FRAV2D face database,2200 images from the FERET database, where the images vary in pose, expression,illumination and scale and 400 images from the ORL face database, where theimages slightly vary in pose. Our method has shown 93.3%, 88.5% and 99%recognition accuracy for the FRAV2D, FERET and the ORL database respectively.

Face Recognition using Hough Peaks extracted from the significant blocks of the Gradient Image