A Classification of Internet Pornographic Images

Abstract

Internet pornography (Internet Porn) is addictive to teenagers and kids around the world. The normal practice is to block those websites or filter out pornography from kids. Many research papers have been published how to detect a human pornographic image on web pages. A new technique was proposed here to classify pornography images using range of YCbCr (colour feature) and three new measurements: %Face_Area, %AHB and Rmax. A computer algorithm such as C4.5 was applied to construct a decision tree. The main contribution of this paper is simplicity that retains high accuracy within an acceptable processing time. The accuracy of experimental results was 85.2% with an average processing time of 0.21314 seconds per image. To cite this document: Chetneti Srisa-an, "A classification of internet pornographic images", International Journal of Electronic Commerce Studies, Vol.7, No.1, pp.95-104, 2016. Permanent link to this document: http://dx.doi.org/10.7903/ijecs.1408