Citation

Zaidan, A. A. and Abdul Karim, Hezerul and Ahmad, Nurul Nadia and Zaidan, B. B. and Sali, Aduwati (2014) A four-phases methodology to propose anti-pornography system based on neural and bayesian methods of artificial intelligence. International Journal of Pattern Recognition and Artificial Intelligence, 28 (1). ISSN 0218-0014

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Abstract

Pornographic images are disturbing and malicious contents that are easily available through Internet technology. It has a negative and lasting effect on children who use the Internet; thus, pornography has become a serious threat not only to Internet users but also to society at large. Therefore, developing efficient and reliable tools to automatically filter pornographic contents is imperative. However, the effective interception of pornography remains a challenging issue. In this paper, a four-phase anti-pornography system based on the neural and Bayesian methods of artificial intelligence is proposed. Primitive information on pornography is examined and then used to determine if a given image falls under the pornography category. First, we present a detailed description of preliminary study phase followed by the modeling phase for the proposed skin detector. An anti-pornography system is created in the development phase, which also includes the proposed pornography classifier based on skin detection. Finally, the performance assessment method for the proposed anti-pornography system is discussed in the evaluation phase.

Item Type:	Article
Uncontrolled Keywords:	Anti-pornography, skin detector, pornography classifier, neural network, Bayesian method
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	06 May 2014 05:19
Last Modified:	01 Feb 2017 05:12
URII:	http://shdl.mmu.edu.my/id/eprint/5462

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