DocumentCode :
3314300
Title :
A universal and robust human skin color model using neural networks
Author :
Phung, Son Lam ; Chai, Douglas ; Bouzerdoum, Abdesselam
Author_Institution :
Visual Inf. Process. Group, Edith Cowan Univ., Joondalup, WA, Australia
Volume :
4
fYear :
2001
fDate :
2001
Firstpage :
2844
Abstract :
We propose a new image classification technique that utilizes neural networks to classify skin and non-skin pixels in color images. The aim is to develop a universal and robust model of the human skin color that caters for all human races. The ability to detecting solid skin regions in color images by the model is extremely useful in applications such as face detection and recognition, and human gesture analysis. Experimental results show that the neural network classifiers can consistently achieve up to 90% accuracy in skin color detection
Keywords :
computer vision; face recognition; image classification; image colour analysis; multilayer perceptrons; color images; face detection; face recognition; human skin color model; image classification; multilayer perceptron; neural networks; Color; Face detection; Face recognition; Humans; Image classification; Neural networks; Pixel; Robustness; Skin; Solid modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-7044-9
Type :
conf
DOI :
10.1109/IJCNN.2001.938827
Filename :
938827
Link To Document :
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