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A Robust & Fast Face Detection System

, and . ACEEE International Journal on Signal & Image Processing, 1 (3): 6 (December 2010)

Abstract

Human face detection is a significant problem of image processing and is usually a first step for face recognition and visual surveillance. This paper presents the details of face detection approach that is implemented to achieve accurate face detection in group color images which are based on facial feature and Support Vector Machine. In the first step, the proposed approach quickly separates skin color regions from the background and from non-skin color regions using YCbCr color space transformation. After the detection of skin regions, the images are processed with, wavelet transforms (WT) and discrete cosine transforms (DCT) as a result of which the 30×30 pixel sub images are found. These sub images are then assigned to SVM classifier as an input. The SVM is used to classify non-face regions from the remaining regions more accurately, that are obtained from previous steps and having big difference between faces regions and non-faces regions. The experimental results on different types of group color images show that this approach improves the detection speed and minimizes the false detection rate in less time and detects faces in different color images.

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