Fast adaptive skin detection in JPEG images

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Abstract

Skin region detection plays an important role in a variety of applications such as face detection, adult image filtering and gesture recognition. To improve the accuracy and speed of skin detection, in this paper, we describe a fast adaptive skin detection approach that works on DCT domain of JPEG image and classifies each image block according to its color and texture properties. Main contributions of our skin detector are: 1) It jointly takes into consideration the color and texture characteristics of human skin for classification and can adaptively control the detection threshold according to image content; 2) It requires no full decompression of JPEG compressed images and directly derives color and texture features of each image block from DCT coefficients. Comparisons with other existing skin detection techniques demonstrate that our algorithm can compute very fast and achieve good accuracy. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Zheng, Q. F., & Gao, W. (2005). Fast adaptive skin detection in JPEG images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3768 LNCS, pp. 595–605). https://doi.org/10.1007/11582267_52

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