Automatic Detection of Human Nudes
International Journal of Computer Vision - 1998 Marr Prize
Neural Networks for Web Content Filtering
IEEE Intelligent Systems
Classifying Objectionable Websites Based on Image Content
IDMS '98 Proceedings of the 5th International Workshop on Interactive Distributed Multimedia Systems and Telecommunication Services
Non-retrieval: Blocking Pornographic Images
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Classifying offensive sites based on image content
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
WebGuard: A Web Filtering Engine Combining Textual, Structural, and Visual Content-Based Analysis
IEEE Transactions on Knowledge and Data Engineering
A Novel Web Page Filtering System by Combining Texts and Images
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
The Filtering of Internet Images Based on Detecting Erotogenic-part
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 02
Pornographic Images Detection Based on CBIR and Skin Analysis
SKG '08 Proceedings of the 2008 Fourth International Conference on Semantics, Knowledge and Grid
Skin segmentation based on cellular learning automata
Proceedings of the 6th International Conference on Advances in Mobile Computing and Multimedia
Data Mining with Decision Trees: Theroy and Applications
Data Mining with Decision Trees: Theroy and Applications
An intelligent categorization engine for bilingual web content filtering
IEEE Transactions on Multimedia
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In this paper we address classification of Web content and in particular its application in the detection of pornographic Web pages. Filtering of undesirable Web content is mainly achieved based on blocking a specific Web address via searching it in a reference list of black URLs or doing a plain contextual analysis on the page by searching special keywords in the text. The main problem with current filtering methods is the requirement for instantly update of the URL list and also the high rate of over-blocking the usual pages. In this paper, we propose an intelligent approach which is based on using textual, profile, and visual features in a hierarchical structure classifier. Textual features contain information about keywords, black-words, etc. and profile features contain structural information like number of links, meta-tags, pictures, etc. As for the visual features we employ a sort of global and local indicative features including topological and shape-based characteristics which are extracted from the skin region. The algorithm was applied on a dataset with 1295 Web pages as training set including 700 porn pages (coming with text, image, or both) in English and Persian, and 595 non-porn pages including pages with medical, health, sports, etc. topics. Using a test dataset with 290 Web-ages a 95% accuracy rate was obtained.