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PORNOGRAPHIC IMAGE DETECTION BASED ON MULTILEVEL REPRESENTATION
Wang, Yushi ; Huang, Qingming ; Gao, Wen
刊名international journal of pattern recognition and artificial intelligence
2009
关键词Image classification pornographic images visual word visual phrase multilevel representation SKIN DETECTION RETRIEVAL SYSTEM DISCOVERY PATTERNS REGION MODELS SCALE WORDS
DOI10.1142/S0218001409007739
英文摘要With the proliferation of pornographic images on the Internet, it is essential to automatically detect pornographic images by analyzing image content. Most traditional detection systems are based on low-level features and generate many false positives due to images that contain large regions of skin-like colors. In this paper, we present a novel detection method based on local features, such as SIFT (Scale Invariant Feature Transform) visual words. Support Vector Machine (SVM) is used to classify images according to their multilevel representation based on visual words and the distribution of pornography-related visual words. The multilevel representation captures inter-word statistics and fuses various visual components of pornographic scenes. Experimental results demonstrate that our method outperforms traditional skin-region and human-body-model based methods, and performs well on a wide range of test data, in particular, on human-related images.; Computer Science, Artificial Intelligence; SCI(E); EI; 4; ARTICLE; 8; 1633-1655; 23
语种英语
内容类型期刊论文
源URL[http://ir.pku.edu.cn/handle/20.500.11897/396143]  
专题信息科学技术学院
推荐引用方式
GB/T 7714
Wang, Yushi,Huang, Qingming,Gao, Wen. PORNOGRAPHIC IMAGE DETECTION BASED ON MULTILEVEL REPRESENTATION[J]. international journal of pattern recognition and artificial intelligence,2009.
APA Wang, Yushi,Huang, Qingming,&Gao, Wen.(2009).PORNOGRAPHIC IMAGE DETECTION BASED ON MULTILEVEL REPRESENTATION.international journal of pattern recognition and artificial intelligence.
MLA Wang, Yushi,et al."PORNOGRAPHIC IMAGE DETECTION BASED ON MULTILEVEL REPRESENTATION".international journal of pattern recognition and artificial intelligence (2009).
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