Paper
25 February 2005 Fast skin color detector for face extraction
Lihui Chen, Christos Grecos
Author Affiliations +
Proceedings Volume 5671, Real-Time Imaging IX; (2005) https://doi.org/10.1117/12.585341
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
Human face detection is the first step for a fully automated face recognition system. It is also crucial to video surveillance systems, human computer interface, image/video retrieval systems. We consider color a very useful cue for face detection in color images. So that we propose a fast skin color detector for detecting in skin color patches in images with complex illumination and background. The accuracy and performance of this detector will have great affect on the upcoming feature extraction and verification processing. In our architecture, after applying a novel adaptive lighting compensation to alleviate the correct the illumination, a skin color filter based on normalized RGB color space is used to detect skin tone patches. Then, in order to remove noises and increase accuracy, morphological operations are used to refine the mask generated by the filter. Finally, the refined mask is used to gain the final result. For each step, including lighting compensation, color space modeling and final results, when compared to existing skin-tone color filtering algorithms, our algorithm is proven to be more robust and efficient by algorithm analysis and experiments results. After the processing, data amount is dramatically reduced and later algorithms can start with the skin patches remained.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lihui Chen and Christos Grecos "Fast skin color detector for face extraction", Proc. SPIE 5671, Real-Time Imaging IX, (25 February 2005); https://doi.org/10.1117/12.585341
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Skin

Facial recognition systems

RGB color model

Optical filters

Light sources and illumination

Sensors

Image filtering

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