Agent based pornography filtering system

Internet is an infinite information repository that also contains harmful contents like; pornography, violence, and hate messages. It is very important to obstruct these kinds of contents from underage children not to adversely affect their development. Today, there are many commercial software products developed for this purpose. But the filtering capabilities of these commercial software are limited to text based and image based contents. Different techniques must be used to filter video based contents. This article describes an agent-based system which is developed for the detection of videos containing pornographic contents. Videos on the Internet can be divided into six groups as; anime, commercial, music, sitcom, sports, and porn related. The proposed system uses the Hidden Markov Model (HMM) based classification technique to classify the videos into these predefined categories with intelligent agents. Color features are extracted from each video frame and used as observation sequences in HMM for classification. According to the classification results, the videos, which are closely related to the category of sex and pornography, are filtered to the underage users. The test results obtained indicate that the classification has been satisfactory.