2008 Second International Conference on Future Generation Communication and Networking Symposia 2008
DOI: 10.1109/fgcns.2008.41
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HSV Color Space and Face Detection Based Objectionable Image Detecting

Abstract: Internet access has dramatically increased the risk of receiving objectionable information such as the pornographic images. Content based Image detection is of the paramount importance in objectionable images filtering in Internet. This paper designed a simplified system by using the HSV color space converted by the law of gravity center and combining the face detection to define and evaluate the degree of the the benign image in general.

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Cited by 8 publications
(3 citation statements)
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References 7 publications
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“…Compared with most of benign images, a large number of exposed skin regions appear in pornographic images. It is easy to obtain the location of the exposed human genitals by analysing these regions [16–18]. In the proposed method, the skin colour regions of pornographic images are detected in compressed domain at first [17].…”
Section: Proposed Pornographic Images Region Detection Methods In Comentioning
confidence: 99%
“…Compared with most of benign images, a large number of exposed skin regions appear in pornographic images. It is easy to obtain the location of the exposed human genitals by analysing these regions [16–18]. In the proposed method, the skin colour regions of pornographic images are detected in compressed domain at first [17].…”
Section: Proposed Pornographic Images Region Detection Methods In Comentioning
confidence: 99%
“…Next, ROI module segments the hand from background by using skin color. The minimum and maximum skin ranges are Hue = 0 -20, Saturation = 30 -150, and Value = 80 -255 [17] [18]. The skin color pixels, which have the values between these ranges, are selected.…”
Section: System Architecturementioning
confidence: 99%
“…So various authors have used different color spaces for information retrieval Huang et al [17], Chen et al [18], Zhao et al [19],Yuzheng et al [20], Anari et al [21] used HSV color space for segmentation. Combination of color spaces [22][23][24][25][26][27][28] also yielded good results.…”
Section: Introductionmentioning
confidence: 99%