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2013 | OriginalPaper | Buchkapitel

40. Illicit Image Detection: An MRF Model Based Stochastic Approach

verfasst von : Mofakharul Islam, Paul Watters, John Yearwood, Mazher Hussain, Lubaba A. Swarna

Erschienen in: Innovations and Advances in Computer, Information, Systems Sciences, and Engineering

Verlag: Springer New York

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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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Metadaten
Titel
Illicit Image Detection: An MRF Model Based Stochastic Approach
verfasst von
Mofakharul Islam
Paul Watters
John Yearwood
Mazher Hussain
Lubaba A. Swarna
Copyright-Jahr
2013
Verlag
Springer New York
DOI
https://doi.org/10.1007/978-1-4614-3535-8_40

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