2017
DOI: 10.3390/e19010026
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Face Detection Based on Skin Color Segmentation Using Fuzzy Entropy

Abstract: Face detection is the first step of any automated face recognition system. One of the most popular approaches to detect faces in color images is using a skin color segmentation scheme, which in many cases needs a proper representation of color spaces to interpret image information. In this paper, we propose a fuzzy system for detecting skin in color images, so that each color tone is assumed to be a fuzzy set. The Red, Green, and Blue (RGB), the Hue, Saturation and Value (HSV), and the YCbCr (where Y is the lu… Show more

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Cited by 25 publications
(11 citation statements)
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“…Based on Equations (10) and (11), the entropy can be calculated as follows: where i = 1 and 2. Based on the maximum entropy criterion [ 41 , 42 ], the optimal parameters of of feature i are calculated by being selected when the entropy is maximized. From this, the input membership functions of features 1 and 2 are defined as shown in Figure 9 .…”
Section: Proposed Methodsmentioning
confidence: 99%
“…Based on Equations (10) and (11), the entropy can be calculated as follows: where i = 1 and 2. Based on the maximum entropy criterion [ 41 , 42 ], the optimal parameters of of feature i are calculated by being selected when the entropy is maximized. From this, the input membership functions of features 1 and 2 are defined as shown in Figure 9 .…”
Section: Proposed Methodsmentioning
confidence: 99%
“…Authors proposed a fuzzy system to detect human skin color [2]. The proposed method accepts RGB, HSV, and YCbCr color space to develop the design and assume each color space as a fuzzy set.…”
Section: Related Workmentioning
confidence: 99%
“…Zhang et al [14] proposed a novel saliency detection model using both color and texture features and incorporating higher-level priors, and calculated color saliency map and texture saliency map based on the region contrast method and adaptive weight. Pujol et al [15] proposed a fuzzy system for detecting skin in color images to realize automated face recognition. Hoshino et al [16] designed a detection algorithm to capture subtle differences in colors through a free iPhone application to identify acholic stools in infants with biliary atresia.…”
Section: Current Color Discrimination Systemmentioning
confidence: 99%