Recognition of Pornographic Web Pages by Classifying Texts and Images

—With the rapid development of the World Wide Web, people benefit more and more from the sharing of information. However, Web pages with obscene, harmful, or illegal content can be easily accessed. It is important to recognize such unsuitable, offensive, or pornographic Web pages. In this paper, a novel framework for recognizing pornographic Web pages is described. A C4.5 decision tree is used to divide Web pages, according to content representations, into continuous text pages, discrete text pages, and image pages. These three categories of Web pages are handled, respectively, by a continuous text classifier, a discrete text classifier, and an algorithm that fuses the results from the image classifier and the discrete text classifier. In the continuous text classifier, statistical and semantic features are used to recognize pornographic texts. In the discrete text classifier, the naive Bayes rule is used to calculate the probability that a discrete text is pornographic. In the image...

• Type: Journal
• Year: 2007
• Where: PAMI
• Authors: Weiming Hu, Ou Wu, Zhouyao Chen, Zhouyu Fu, Stephen J. Maybank
• Keywords: Discrete Text Classifier, PAMI 2007, Text Classifier, Web Pages