A color image segmentation algorithm by using region and edge information

Authors:
Yuchou Chang;Yue Zhou;Yonggang Wang;Yi Hong
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanhai Jiaotong University, Shanghai, P.R. China;Institute of Image Processing and Pattern Recognition, Shanhai Jiaotong University, Shanghai, P.R. China;Institute of Image Processing and Pattern Recognition, Shanhai Jiaotong University, Shanghai, P.R. China;Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, P.R. China
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

Citing 3
Cited 0

Unsupervised Segmentation of Color-Texture Regions in Images and Video

IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised video object segmentation and tracking based on new edge features

Pattern Recognition Letters
Color quantization and processing by Fibonacci lattices

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

A novel segmentation algorithm for natural color image is proposed. Fibonacci Lattice-based Sampling is used to get the symbols of image so as to make each pixel’s label containing color information rather than only as a class marker. Next, Region map is formed based on Fibonacci Lattice symbols to depict homogeneous regions. On the other hand, by applying fuzzy homogeneity algorithm on the image, we filter it to acquire Edge map. To strengthen the ability of discrimination, both the weighted maps are combined to form Region-Edge map. Based on above processes, growing-merging method is used to segment the image. Finally, experiments show very promising results.