A Novel Color Space Creating Method Applied to Skin Color Detection

Author(s):  
Seyyed Meysam Hosseini ◽  
Hadi Sadoghi Yazdi ◽  
Saber Amjadi ◽  
H. Farsi
2013 ◽  
Vol 756-759 ◽  
pp. 1938-1942 ◽  
Author(s):  
Yi Ting Wang ◽  
Feng Jing Shao

Aiming at the shortcomings of hand gestures segmentation based on fixed threshold and the problem of the interference of background color, this paper proposes a research on hand gestures segmentation based on skin color detection. The captured image is translated to YCgCr color space from RGB color space, and then skin color segmentation is done by using dynamic threshold method, so the hand gestures segmentation is completed. Finally segmentation results are verified by experiments and the method is summarized.


2013 ◽  
Vol 756-759 ◽  
pp. 3517-3521
Author(s):  
Xue Feng Dong

The main objective of designing skin color model is to determine whether the pixel is skin color pixels and generate the skin color mask images. The paper discusses the choise of color space and skin color model designing in skin color detection system, analysis the problems often needed to solve in it and put forward an improved skin color detection algorithm model based on ellipse boundary. The skin color detection experiment is completed. The result of experiment shows the skin color detection algorithm model is good.


2015 ◽  
Vol 57 ◽  
pp. 41-48 ◽  
Author(s):  
Khamar Basha Shaik ◽  
P. Ganesan ◽  
V. Kalist ◽  
B.S. Sathish ◽  
J. Merlin Mary Jenitha

2012 ◽  
Vol 263-266 ◽  
pp. 525-528
Author(s):  
Hua Yun Yu ◽  
Meng Yun Liu

In order to improve the accuracy and speed of the color detection, to comparative analysis on skin color detection in the clustering of nine color space and regularity of distribution area, and some meaningful conclusions are discovered that the XYZ color space is suitable to do skin color two-dimensional threshold segmentation while the HSV、HIS、HSL is suitable to do one-dimensional threshold segmentation on tonal H component. A new color space xy-H is constructed for color detection using those conclusions which were discovered. The results show that it has significantly improved for color diction.


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