DocumentCode :
2872083
Title :
A Robust Method for Skin Detection and Segmentation of Human Face
Author :
Wang, Baozhu ; Chang, Xiuying ; Liu, Cuixiang
Author_Institution :
Sch. of Inf. & Eng., Hebei Univ. of Technol., Tianjin, China
fYear :
2009
fDate :
1-3 Nov. 2009
Firstpage :
290
Lastpage :
293
Abstract :
This paper presents the procedure of skin detection and segmentation which can find out arbitrarily tilted human faces in color images. Face segmentation is based on skin detection through the establishment of skin model. First, a method for compensating the color of the input images is used to alleviate the interferences from bad illuminating conditions; secondly, a skin model about skin information is used to detect skin pixels in color images; thirdly, a new algorithm of segmentation integrated histogram with otsu is used to find out the skin regions in binary images; finally, mathematical morphology operator and prior knowledge are used to point out the face regions and discard regions that are similar to the skin in color. This method can handle various sizes of faces, different illumination conditions, diverse pose and changeable expression. In particular, the scheme significantly increases the execution speed of the face segmentation algorithm in the case of complex backgrounds.
Keywords :
face recognition; image colour analysis; image segmentation; mathematical morphology; color images; human face segmentation; mathematical morphology; skin pixel detection; Color; Face detection; Histograms; Humans; Image segmentation; Interference; Mathematical model; Pixel; Robustness; Skin; adaptive threshold segmentation; color balance; gray-scale image enhancement; space conversion Gaussian model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-5557-7
Electronic_ISBN :
978-0-7695-3852-5
Type :
conf
DOI :
10.1109/ICINIS.2009.80
Filename :
5366722
Link To Document :
بازگشت