By Topic

A web pornography patrol system by content-based analysis: In particular text and image

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Polpinij, J. ; Fac. of Inf., Mahasarakham Univ., Maha Sarakham ; Sibunruang, C. ; Paungpronpitag, S. ; Chamchong, R.
more authors

A problem of children being exposed to pornographic Web sites on the Internet has led to their safety issues. To prevent the children from these inappropriate materials, an effective Web filtering system is essential. Content-based Web filtering is one of the important techniques to handle and filter inappropriate information on the web. In this paper, we examine a content-based analysis technique to filter the pornographic Web sites. Then, our system consists of two primary content-based filtering techniques such as text and image. For text analysis, the support vector machine (SVM) algorithm and N-gram model based on Bayes' theorem is applied and experimented to filter pornographic text for both Thai and English language web sites. Meanwhile, we build and examine an image filtering system with a hierarchical image filtering method. It consists of two main processes such as normalized R/G ratio which is using the pixel ratios (red and green color channels) and human composition matrix (HCM) based on skin detection. The empirical results show that our analysis methods of text and image are more effective for pornographic Web filtering. Finally, we have modeled a pornographic web filter using content-based analysis into our Anti-X system.

Published in:

Systems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on

Date of Conference:

12-15 Oct. 2008