- Volume 18 Issue 7
DOI QR Code
Robust Skin Area Detection Method in Color Distorted Images
색 왜곡 영상에서의 강건한 피부영역 탐지 방법
- Hwang, Daedong (Research Center, Bosung Tech.,Inc.) ;
- Lee, Keunsoo (Dept. of Computer Science & Engineering (Computer System Institute), Hankyong National University)
- Received : 2017.05.29
- Accepted : 2017.07.07
- Published : 2017.07.31
With increasing attention to real-time body detection, active research is being conducted on human body detection based on skin color. Despite this, most existing skin detection methods utilize static skin color models and have detection rates in images, in which colors are distorted. This study proposed a method of detecting the skin region using a fuzzy classification of the gradient map, saturation, and Cb and Cr in the YCbCr space. The proposed method, first, creates a gradient map, followed by a saturation map, CbCR map, fuzzy classification, and skin region binarization in that order. The focus of this method is to rigorously detect human skin regardless of the lighting, race, age, and individual differences, using features other than color. On the other hand,the borders between these features and non-skin regions are unclear. To solve this problem, the membership functions were defined by analyzing the relationship between the gradient, saturation, and color features and generate 108 fuzzy rules. The detection accuracy of the proposed method was 86.35%, which is 2~5% better than the conventional method.
fuzzy;image processing;skin detection
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