Abstract
This paper is concerned with estimating a probability density function of human skin color using a finite Gaussian mixture model whose parameters are estimated through the EM algorithm. Hawkins' statistical test on the normality and homoscedasticity (common covariance matrix) of the estimated Gaussian mixture models is performed and McLachlan's bootstrap method is used to test the number of components in a mixture. Experimental results show that the estimated Gaussian mixture model fits skin images from a large database. Applications of the estimated density function in image and video databases are presented.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 458-466 |
| Number of pages | 9 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 3656 |
| State | Published - 1999 |
| Event | Proceedings of the 1999 7th Conference of the Storage and Retrieval for Image and Video Databases VII - San Jose, Ca, USA Duration: Jan 26 1999 → Jan 29 1999 |
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering