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http://dx.doi.org/10.15207/JKCS.2019.10.5.001

A Study on the Improvement of Skin Loss Area in Skin Color Extraction for Face Detection  

Kim, Dong In (Dept of Plasma Bio Display, KwangWoon University)
Lee, Gang Seong (Ingenium College of Liberal Arts, KwangWoon University)
Han, Kun Hee (Division of Information & Communication Engineering, Baekseok University)
Lee, Sang Hun (Ingenium College of Liberal Arts, KwangWoon University)
Publication Information
Journal of the Korea Convergence Society / v.10, no.5, 2019 , pp. 1-8 More about this Journal
Abstract
In this paper, we propose an improved facial skin color extraction method to solve the problem that facial surface is lost due to shadow or illumination in skin color extraction process and skin color extraction is not possible. In the conventional HSV method, when facial surface is brightly illuminated by light, the skin color component is lost in the skin color extraction process, so that a loss area appears on the face surface. In order to solve these problems, we extract the skin color, determine the elements in the H channel value range of the skin color in the HSV color space among the lost skin elements, and combine the coordinates of the lost part with the coordinates of the original image, To minimize the number of In the face detection process, the face was detected using the LBP Cascade Classifier, which represents texture feature information in the extracted skin color image. Experimental results show that the proposed method improves the detection rate and accuracy by 5.8% and 9.6%, respectively, compared with conventional RGB and HSV skin color extraction and face detection using the LBP cascade classifier method.
Keywords
HSV color conversion; LBP; Cascade Classifier; skin color extraction; Face detection;
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Times Cited By KSCI : 9  (Citation Analysis)
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