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

M. R. Tabassum, A. Ul Gias, M. M. Kamal, M. S. Islam, H. M. Muctadir, M. Ibrahim, A. K. Shakir, A. Imran, M. S. Islam, M. G. Rabbani, S. M. Khaled, M. S. Islam, Z. Begum

Research output: Contribution to journalArticleAcademicpeer-review

9 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)811-817
Number of pages7
JournalInformation Technology Journal
Issue number4
Publication statusPublished - 2010
Externally publishedYes


  • Color segmentation
  • Color space model
  • Image processing
  • Skin detection


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