A skin detection algorithm based on discrete Cosine transform and generalized Gaussian density

In this paper, we propose a highly efficient algorithm to model the human skin color. The underlying algorithm involves generating a discrete Cosine transform (DCT) at each pixel location, using the surrounding points. These DCT coefficients are assumed to follow a generalized Gaussian distribution...

Full description

Saved in:
Bibliographic Details
Main Authors: Ghouzali, S., Hemami, S., Rziza, M., Aboutajdine, D., Mouaddib, E.M.
Format: Conference Proceeding
Language:English
Subjects:
Color
Detection algorithms
Discrete Cosine Transform
Discrete cosine transforms
Face detection
Generalized Gaussian distribution
Image segmentation
Maximum likelihood estimation
Pixel
Robustness
Shape
Skin
Skin detection
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we propose a highly efficient algorithm to model the human skin color. The underlying algorithm involves generating a discrete Cosine transform (DCT) at each pixel location, using the surrounding points. These DCT coefficients are assumed to follow a generalized Gaussian distribution (GGD). Next, the model parameters are estimated using the maximum-likelihood (ML) criterion applied to a set of training skin samples. Finally, each pixel is classified as skin or the opposite if its likelihood ratio is above some threshold. The experimental results show that our model avoids excessive false detection while still retaining a high degree of correct detection.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2008.4711827