Face detection architecture design using hybrid skin color detection and cascade of classifiers

This paper presents an efficient face detection algorithm which results in low cost and high performance hardware implementation. Using the proposed scheme of hybrid skin color detection and cascade of classifiers, we successfully overcome (i) the poor false positive rate issue in the skin color based face detection and (ii) the huge computation complexity in the cascade of classifiers. A light variation tolerable skin color detection method and a scan-line based dynamic down-sampling architecture are also proposed to enhance the performance. Experimental results reveal that the proposed design has high detection accuracy with low hardware cost as compared with related work.