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Adult Image Classification using Adaptive Skin Detection and Edge Information  

Park, Chan-Woo (Dept. of Comp. Sci. & Eng., Hanyang University)
Park, Ki-Tae (Ambient Intelligence Software Team, Institute of Hanyang University)
Moon, Young-Shik (Dept. of Comp. Sci. & Eng., Hanyang University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.48, no.1, 2011 , pp. 127-132 More about this Journal
Abstract
In this paper, we propose a novel method of adult image classification by combining skin color regions and edges in an input image. The proposed method consists of four steps. In the first step, initial skin color regions are detected by logical AND operation of all skin color regions detected by the existing methods of skin color detection. In the second step, a skin color probability map is created by modeling the distribution of skin color in the initial regions. Then, a binary image is generated by using threshold value from the skin color probability map. In the third step, after using the binary image and edge information, we detect final skin color regions using a region growing method. In the final step, adult image classification is performed by support vector machine(SVM). To this end, a feature vector is extracted by combining the final skin color regions and neighboring edges of them. As experimental results, the proposed method improves performance of the adult image classification by 9.6%, compared to the existing method.
Keywords
Adult Image Classification; Adaptive Skin Detection; SVM;
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