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Innovations and Advances in Computer, Information, Systems Sciences, and Engineering pp 467–479Cite as

Illicit Image Detection: An MRF Model Based Stochastic Approach

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 152))

Abstract

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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Author information

Authors and Affiliations

  1. Internet Commerce and Security Laboratory, School of Science, Information Technology and Engineering, University of Ballarat, Ballarat, VIC, Australia

    Mofakharul Islam, Paul Watters & John Yearwood

  2. Melbourne Institute of Technology, Melbourne, VIC, Australia

    Mazher Hussain

  3. IBM Australia, Ballarat, VIC, Australia

    Lubaba A. Swarna

Authors
  1. Mofakharul Islam
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  2. Paul Watters
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  3. John Yearwood
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  4. Mazher Hussain
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  5. Lubaba A. Swarna
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Corresponding author

Correspondence to Mofakharul Islam .

Editor information

Editors and Affiliations

  1. School of Engineering, University of Bridgeport, University Avenue 221, Bridgeport, 06604, Connecticut, USA

    Khaled Elleithy

  2. School of Engineering, University of Bridgeport, University Avenue 221, Bridgeport, 06604, Connecticut, USA

    Tarek Sobh

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Islam, M., Watters, P., Yearwood, J., Hussain, M., Swarna, L.A. (2013). Illicit Image Detection: An MRF Model Based Stochastic Approach. In: Elleithy, K., Sobh, T. (eds) Innovations and Advances in Computer, Information, Systems Sciences, and Engineering. Lecture Notes in Electrical Engineering, vol 152. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3535-8_40

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  • DOI: https://doi.org/10.1007/978-1-4614-3535-8_40

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-3534-1

  • Online ISBN: 978-1-4614-3535-8

  • eBook Packages: EngineeringEngineering (R0)

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