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Face detection using fuzzy color classifier and convex-hull  

Park, Min-Sik (Dept.of Electric Electronics Engineering, Yonsei University)
Park, Chang-U (Dept.of Electric Electronics Engineering, Yonsei University)
Kim, Won-Ha (Professor. Dept. of Information and Communication Engineering )
Park, Min-Yong (Dept.of Electric Electronics Engineering, Yonsei University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.39, no.2, 2002 , pp. 69-78 More about this Journal
Abstract
This paper addresses a method to automatically detect out a person's face from a given image that consists of a hair and face view of the person and a complex background scene. Out method involves an effective detection algorithm that exploits the spatial distribution characteristics of human skin color via an adaptive fuzzy color classifier (AFCC), The universal skin-color map is derived on the chrominance component of human skin color in Cb, Cr and their corresponding luminance. The desired fuzzy system is applied to decide the skin color regions and those that are not. We use RGB model for extracting the hair color regions because the hair regions often show low brightness and chromaticity estimation of low brightness color is not stable. After some preprocessing, we apply convex-hull to each region. Consequent face detection is made from the relationship between a face's convex-hull and a head's convex-hull. The algorithm using the convex-hull shows better performance than the algorithm using pattern method. The performance of the proposed algorithm is shown by experiment. Experimental results show that the proposed algorithm successfully and efficiently detects the faces without constrained input conditions in color images.
Keywords
Face detection; convex-hull; fuzzy system; color classifier;
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