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Conference Paper Adult image detection with c lose-up face classification
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Authors
Byeong Cheol Choi, Jeong Nyeo Kim, Jea Cheol Ryou
Issue Date
2009-01
Citation
International Conference on Consumer Electronics (ICCE) 2009, pp.1-2
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICCE.2009.5012282
Abstract
The SVM (support vector machine) and the SCM (skin color model) are used for detection of adult contents. The SVM consists of multi-class learning model and is very effective method for face detection, but complex. On the contrary, the SCM is very simple for detecting the adult images using skin ratio derived from statistical characteristics of RGB color information, but less effective in close-up facial images. So, we propose a hybrid scheme that combines the SVM for the 1st filtering scheme using 3-class learning model (with classes of objectionable, non-objectionable and close-up facial image) with the SCM for the 2nd filtering scheme using skin ratio. The performance of proposed scheme improves about 2.5% ~ 4.6% in the true positive rate and about 4.6% in the false positive rate. © 2009 IEEE.
KSP Keywords
Color information, Face Classification, Facial image, False Positive(FP), False Positive Rate, Hybrid scheme, RGB color, Statistical characteristics, Support VectorMachine(SVM), True positive rate, adult image detection