Classifying Objectionable Websites Based on Image Content

This paper describes IBCOW Image-based Classi cation of Objectionable Websites, a system capable of classifying a website as objectionable or benign based on image content. The system uses WIPETM Wavelet Image Pornography Elimination and statistics to provide robust classi cation of on-line objectionable World Wide Web sites. Semantically-meaningful feature vector matching is carried out so that comparisons between a given on-line image and images marked as "objectionable" and "benign" in a training set can be performed efciently and e ectively in the WIPE module. If more than a certain number of images sampled from a site is found to be objectionable, then the site is considered to be objectionable. The statistical analysis for determining the size of the image sample and the threshold number of objectionable images is given in this paper. The system is practical for real-world applications, classifying a Web site at a speed of less than 2 minutes each, including t...

• Type: Conference
• Year: 1998
• Where: IDMS
• Authors: James Ze Wang, Jia Li, Gio Wiederhold, Oscar Firschein
• Keywords: Classi Cation, IDMS 1998, Image-based Classi Cation, Images, Multimedia