DocumentCode :
3459545
Title :
Human Face Detection Based on SOFM Neural Network
Author :
Kun, Yang ; Hong, Zhu ; Ying-jie, Pan
Author_Institution :
Inst. of Inf. & Autom. Eng., Xi´´an Univ. of Technol., Shaanxi
fYear :
2006
fDate :
20-23 Aug. 2006
Firstpage :
1253
Lastpage :
1257
Abstract :
This paper presented a new method of human face detection using Kohonen self-organized feature map (SOFM) neural network (NN). Presently, the human face detection based on the skin color is one of the main methods, but the most of color images include a lot of the skin-like information. Therefore, it is a difficult problem how to effectively extract the skin regions from the skin-like regions. The paper presented the detection method based on SOFM neural network to solve the problem. After nonlinear color clustering, skin regions can be roughly segmented from the skin-like regions and then human face regions can be accurately located by the morphology and the human face features. The experimental results show that the method can accurately detect human face in static color images and has stronger robustness to various skin colors
Keywords :
face recognition; feature extraction; image colour analysis; image segmentation; pattern clustering; self-organising feature maps; skin; Kohonen self-organized feature map; SOFM neural network; human face detection; nonlinear color clustering; skin region segmentation; static color images; Color; Data mining; Face detection; Humans; Image segmentation; Lighting; Morphology; Neural networks; Shape; Skin; Color clustering; Human face detection; Morphology; SOFM NN;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Acquisition, 2006 IEEE International Conference on
Conference_Location :
Weihai
Print_ISBN :
1-4244-0528-9
Electronic_ISBN :
1-4244-0529-7
Type :
conf
DOI :
10.1109/ICIA.2006.305929
Filename :
4097862
Link To Document :
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