A Fast Algorithm for Color Image Segmentation

Authors:
Liju Dong;Philip Ogunbona;Wanqing Li;Ge Yu;Linan Fan;Gang Zheng
Affiliations:
University of Wollongong, Australia;University of Wollongong, Australia;University of Wollongong, Australia;Northeastern University, China;Shenyang University;University of Wollongong, Australia
Venue:
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 2
Year:
2006

Citing 0
Cited 3

An Efficient Gray-level Clustering Algorithm for Image Segmentation

CAR '09 Proceedings of the 2009 International Asia Conference on Informatics in Control, Automation and Robotics
A gray-level clustering reduction algorithm with the least PSNR

Expert Systems with Applications: An International Journal
Fast K-means algorithm based on a level histogram for image retrieval

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.01

Visualization

Abstract

Based on K-means and a two-layer pyramid structure, a fast algorithm is proposed for color image segmentation. The algorithm employs two strategies. Firstly, a two-layer structure of a color image is established. Then, an improved K-means with integer based lookup table implementation is applied to each layer. The clustering result on the upper layer (lower resolution) is used to guide the clustering in the lower layer (higher resolution). Experiments have shown that the proposed algorithm is significantly faster than the original K-means algorithm while producing comparable segmentation results.