Abstract
A new skin segmentation technique for color images is proposed. The proposed technique uses a human skin color model that is based on the Bayesian decision theory and developed using a large training set of skin colors and nonskin colors. The proposed technique is novel and unique in that texture characteristics of the human skin are used to select appropriate skin color thresholds for skin segmentation. Two homogeneity measures for skin regions that take into account both global and local image features are also proposed. Experimental results showed that the proposed technique can achieve good skin segmentation performance (false detection rate of 4.5% and false rejection rate of 4.0%).
| Original language | English |
|---|---|
| Pages (from-to) | 353-356 |
| Number of pages | 4 |
| Journal | Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing |
| Volume | 3 |
| Publication status | Published - 2003 |
| Externally published | Yes |
| Event | 2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong Duration: 6 Apr 2003 → 10 Apr 2003 |