|Title||Comparative study of statistical skin detection algorithms for sub-continental human images|
|Authors||Tabassum, M.R., Gias, A.U., Kamal, M.M., Islam, S., Muctadir, H.M., Ibrahim, M., Shakir, A.K., Imran, A., Islam, S., Rabbani, M.G., Khaled, S.M., Islam, M.S. and Begum, Z.|
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 sub-continental 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 sub-continental skin detection is more suitable with considerable success rate of 91.1% true positives and 88.1% true negatives.
|Journal||Information Technology Journal|
|Journal citation||9 (4), pp. 811-817|
|Publisher||Asian Network for Scientific Information (ANSINET)|
|Digital Object Identifier (DOI)||https://doi.org/10.3923/itj.2010.811.817|