Comparative study of statistical skin detection algorithms for sub-continental human images

被引:5
作者
Tabassum M.R. [1 ]
Gias A.U. [1 ]
Kamal M.M. [1 ]
Islam S. [1 ]
Muctadir H.M. [1 ]
Ibrahim M. [1 ]
Shakir A.K. [1 ]
Imran A. [1 ]
Islam S. [1 ]
Rabbani M.G. [2 ]
Khaled S.M. [1 ]
Islam M.S. [1 ]
Begum Z. [1 ]
机构
[1] Institute of Information Technology, University of Dhaka
[2] Department of Statistics, Biostatistics and Informatics, University of Dhaka
关键词
Color segmentation; Color space model; Image processing; Skin detection;
D O I
10.3923/itj.2010.811.817
中图分类号
学科分类号
摘要
Most of the researches done in the fields of skin detection has been trained and tested on human images of African, Mongolian and Anglo-Saxon ethnic origins for face recognition, human motion detection, pornographic and nude image prediction, etc. Although, there are several intensity invariant approaches to skin detection, the skin color of Indian sub-continentals have not been focused separately. The approach of this research is to make a comparative study between three image segmentation approaches using Indian subcontinental human images, to optimize the detection criteria and to find some efficient parameters to detect the skin area from these images. The experiments observed that HSV color model based approach to Indian subcontinental skin detection is more suitable with considerable success rate of 91.1 % true positives and 88.1 % true negatives. © 2010 Asian Network for Scientific Information.
引用
收藏
页码:811 / 817
页数:6
相关论文
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