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Conference Paper Adult Image Detection using Bayesian Decision Rule weighted by SVM Probability
Cited 23 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Byeong Cheol Choi, Byung Ho Chung, Jae Cheol Ryou
Issue Date
2009-11
Citation
International Conference on Computer Sciences and Convergence Information Technology (ICCIT) 2009, pp.659-662
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICCIT.2009.43
Abstract
The SVM (support vector machine) and the SCM (skin color model) are used in detection of adult contents on images. 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 adult images using skin ratio derived from statistical characteristics of RGB color information, but less effective in close-up facial images. Hence, we propose a hybrid scheme that combines the SVM for the 1st filtering scheme using learning model (with classes of adult, benign and close-up facial images) with the SCM for the 2nd filtering scheme using skin ratio and adaptive MAP (maximum a posterior) hypothesis test based on Bayes' theorem that improves the probability of true positive detection rate of adult images. © 2009 IEEE.
KSP Keywords
Bayes' Theorem, Bayesian Decision, Color information, Decision rules, Facial image, Hybrid scheme, Hypothesis test, Maximum a Posterior(MAP), RGB color, Statistical characteristics, Support VectorMachine(SVM)