Colour image segmentation in various illumination circumstances

Authors:
Chiunhsiun Lin;Ching-Hung Su;Hsuan Shu Huang;Kuo-Chin Fan
Affiliations:
National Taipei University, Taipei, Taiwan;The Department of Electronic Engineering, Lunghwa University of Science and Technology, Taoyuan County, Taiwan;Institute of Computer Science and Information Engineering, National Central University, Jhongli City, Taoyuan County, Taiwan;Institute of Computer Science and Information Engineering, National Central University, Jhongli City, Taoyuan County, Taiwan
Venue:
CSECS '10 Proceedings of the 9th WSEAS international conference on Circuits, systems, electronics, control & signal processing
Year:
2010

Citing 8
Cited 0

A fast algorithm for tracking human faces based on chromatic histograms

Pattern Recognition Letters
Statistical color models with application to skin detection

International Journal of Computer Vision
A Fuzzy-Theory-Based Face Detector

ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Face detection using template matching and skin-color information

Neurocomputing
Face detection in complicated backgrounds and different illumination conditions by using YCbCr color space and neural network

Pattern Recognition Letters
The mixture of K-Optimal-Spanning-Trees based probability approximation: Application to skin detection

Image and Vision Computing
Skin detection using pairwise models

Image and Vision Computing
Skin detection for single images using dynamic skin color modeling

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose a novel colour segmentation algorithm can work in various illumination circumstances. The proposed colour segmentation algorithm operates directly on RGB colour space without the need of colour space transformation and it is very robust to various illumination conditions. Our approach can be employed in various domains (e.g., human skin colour segmentation, the maturity of tomatoes). Furthermore, our approach has the benefits of being insensitive to rotation, scaling, and translation. In addition, the system can be applied to different applications, for example, colour segmentation for fruits (vegetables) quality control by merely changing the values of the parameters (α, β1, β2, γ1. γ2). Experimental results demonstrate the practicability of our proposed approach in colour segmentation.