文章基本信息

标题：Fuzzy Based Skin Detection and Segmentation
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作者：Afia Nazir ; Laiq Hassan ; Alamzeb M. Zai 等
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2013
卷号：10
期号：3
出版社：IJCSI Press
摘要：Skin detection being one of the most crucial tasks in image processing applications, is targeted in this work with special emphasis on fuzzy based skin detection and segmentation techniques. Using weka tool, this paper provides the performance evaluation of two well-known fuzzy based skin detection techniques, fuzzy inference system and Modified Fuzzy C-Mean algorithm (MFCM) on a standard dataset. For the inference system we used the Fuzzy Unordered Rule Induction Algorithm (FURIA) implementation, and Brute Force Search Algorithm implementation for the Modified Fuzzy C-Means algorithm. Based on the experimental results, fuzzy inference algorithm provides 80.4633 % of correct classification for skin pixels and MFCM has 85.2316 % of accuracy in identifying the skin pixels.
关键词：Skin modeling; color space; Fuzzy inference systems; Skin pixels; MFCM; Fuzzy inference system; fuzzy classification.