Conference Paper

Constructing SURF visual-words for pornographic images detection

Lab. of Knowledge Process. & Networked Manuf., Hunan Univ. of Sci. & Technol., Xiangtan, China
DOI: 10.1109/ICCIT.2009.5407272 Conference: Computers and Information Technology, 2009. ICCIT '09. 12th International Conference on
Source: IEEE Xplore

ABSTRACT Pornographic images detection is necessary for us to filter out objectionable information on the Internet. Bag-of-visual-words (BoVW) based pornographic images detection is promising because it can compensate the defect of the traditional approach. However, there are many choices to construct visual-words which are crucial to the tradeoff between the speed and the performance. We propose a novel method of constructing SURF (speeded up robust features) visual-words in skin regions and combining it with color moments. The results show that the performance of SURF visual-words is better than that of SIFT (scale-invariant feature transform) visual-words and our method is more effective to detect pornographic images than many existing methods.

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