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Face Detection based on Skin Color in Image by Neural Networks

Main information
Face detection is one of the challenging problems in the image processing. A novel face detection system is prsented in this paper. The approach relies on skin-based color features extracted from two dimentional Discreate Cosine Transfer (DCT) and neural networks, which can be used to detect faces by using skin color from DCT coefficient of Cb and Cr feature vectors. This system contains the skin color which is the main feature of faces for detection, and then the skin face candidate is examined by using the neural networks, which learn from the feature of faces to classify whether the original image includes a face or not. The processing is based on normalization and Discreate Cosin Transfer. Finally the classification based on neural networks approch. The expriment results on upright frontal color face images from the internt show an exellent detection rate. 
No referenced Knowhow defined
WP5: Detection, Extraction and Annotation of Knowledge. 
School of Informatics University of Bradford  Jianmin Jiang, Ying Weng 
2007-11-05 18:37  Request for more detail


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For educational purposes only - if public document.  For educational purposes only - if public document. 


Protection Status
Copyright School of Informatics, University of Bradford.  Patent Pending. 
Licensing Pending.  Utility Model Pending. 
 
Accepted by IEEE International Conference on Intelligent and Advanced Systems (ICIAS2007) 
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face-detection-based-on-skin-color-in-image-by-neural-networks.pdf
 
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