Illicit Image Detection: An MRF Model Based Stochastic Approach

  • Mofakharul Islam
  • Paul Watters
  • John Yearwood
  • Mazher Hussain
  • Lubaba A. Swarna
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 152)


The steady growth of the Internet, sophisticated digital image processing technology, the cheap availability of storage devices and surfer’s ever-increasing interest on images have been contributing to make the Internet an unprecedented large image library. As a result, The Internet quickly became the principal medium for the distribution of pornographic content favouring pornography to become a drug of the millennium. With the arrival of GPRS mobile telephone technology, and with the large scale arrival of the 3G networks, along with the cheap availability of latest mobile sets and a variety of forms of wireless connections, the internet has already gone to mobile, driving us toward a new degree of complexity. In this paper, we propose a stochastic model based novel approach to investigate and implement a pornography detection technique towards a framework for automated detection of pornography based on contextual constraints that are representatives of actual pornographic activity. Compared to the results published in recent works, our proposed approach yields the highest accuracy in detection.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Mofakharul Islam
    • 1
  • Paul Watters
    • 1
  • John Yearwood
    • 1
  • Mazher Hussain
    • 2
  • Lubaba A. Swarna
    • 3
  1. 1.Internet Commerce and Security Laboratory, School of Science, Information Technology and EngineeringUniversity of BallaratBallaratAustralia
  2. 2.Melbourne Institute of TechnologyMelbourneAustralia
  3. 3.IBM AustraliaBallaratAustralia

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