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Comparative Study of Skin Color based Segmentation Techniques

Noor A. Ibraheem, Rafiqul Z. Khan, Mokhtar M. Hasan Published in Pattern Recognition

International Journal of Applied Information Systems
Year of Publication: 2013
© 2012 by IJAIS Journal
10.5120/ijais13-450985
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  1. Noor A Ibraheem, Rafiqul Z Khan and Mokhtar M Hasan. Article: Comparative Study of Skin Color based Segmentation Techniques. International Journal of Applied Information Systems 5(10):24-34, August 2013. BibTeX

    @article{key:article,
    	author = "Noor A. Ibraheem and Rafiqul Z. Khan and Mokhtar M. Hasan",
    	title = "Article: Comparative Study of Skin Color based Segmentation Techniques",
    	journal = "International Journal of Applied Information Systems",
    	year = 2013,
    	volume = 5,
    	number = 10,
    	pages = "24-34",
    	month = "August",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Segmentation is the classification of the input colored image into skin and non-skin pixels based on skin color information. A wide range of applications that require the segmentation process as a preprocessing operation such as computer vision, face/ hand detection and recognition, medical image analysis, and pattern recognition. Color information is one of the simple cues used for detecting skin color, and the use of proper color space to represent color information of an image is a crucial decision. In this literature different segmentation techniques are presented, examples and comparison between the main three based segmentation techniques are given as well. Skin color modeling based statistical model is explained in detail, with discussion the combination with different segmentation techniques. The selection of appropriate segmentation method depends on the application and system environments. The performance of any segmentation algorithm is quantified using some benchmarking such as recall and precision coefficients, or by calculating the percentage of correct and false detection rates according to the complexion of the technique used.

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Keywords

Color Image Segmentation, Color Space, Pixel Based Segmentation, Edge Based Segmentation, Region Based Segmentation, Gaussian Mixture Model