DocumentCode :
2699381
Title :
Application of rough sets to image pre-processing for Face detection
Author :
Hu, Ming ; Zhang, Qiang ; Wang, Zhiping
Author_Institution :
Liaoning Key Lab. of Intell. Inf. Process., Univ. of Dalian, Dalian
fYear :
2008
fDate :
20-23 June 2008
Firstpage :
545
Lastpage :
548
Abstract :
Both of face detection and Face recognition play important role in the technology of biologic character identify. During processing of face image, it is indispensable to pre-processing. In this paper, a Pre-processing method for face color image based on rough sets theory is put forward. In this method, the image is divided as foreground and background by condition attribution. In order to extract the skin color regions, foreground is segmented by two kinds of the skin color model, YCrCb and HSV color spaces. Then, the opening and closing morphological operation are used to remove the small regions. Experiment shows the new algorithm has been tested by the computer simulation, in terms of accuracy extracting the skin color, positive rate of face detection and error rate etc. The results show that it can improve accuracy of extracting the skin color and shorten operation time validly. The result of enhanced image is better and satisfies requirement of face detection.
Keywords :
face recognition; feature extraction; image colour analysis; image enhancement; image segmentation; rough set theory; biologic character; face color image; face detection; face image processing; face recognition; image enhancement; image preprocessing; rough sets theory; skin color extraction; skin color regions; Color; Computer simulation; Error analysis; Face detection; Face recognition; Image segmentation; Morphological operations; Rough sets; Skin; Testing; condition attribution; face detection; face image preprocessing; indiscernibility relations; rough sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation, 2008. ICIA 2008. International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-2183-1
Electronic_ISBN :
978-1-4244-2184-8
Type :
conf
DOI :
10.1109/ICINFA.2008.4608060
Filename :
4608060
Link To Document :
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