Comparative Study of Statistical Skin Detection Algorithms for Sub-Continental Human Images
Abstract
Object detection has been a focus of research in human-computer interaction. Skin area detection has been a key to different recognitions like face recognition, human motion detection, pornographic and nude image prediction, etc. Most of the research done in the fields of skin detection has been trained and tested on human images of African, Mongolian and Anglo-Saxon ethnic origins. 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.
Cite
@article{arxiv.1008.4206,
title = {Comparative Study of Statistical Skin Detection Algorithms for Sub-Continental Human Images},
author = {Mirza Rehenuma Tabassum and Alim Ul Gias and Md. Mostafa Kamal and Hossain Muhammad Muctadir and Muhammad Ibrahim and Asif Khan Shakir and Asif Imran and Saiful Islamm and Md. Golam Rabbani and Shah Mostafa Khaled and Md. Saiful Islam and Zerina Begum},
journal= {arXiv preprint arXiv:1008.4206},
year = {2010}
}
Comments
8 pages