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Application of image segmentation algorithm based on particle swarm optimization and rough entropy standard

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2 Author(s)
Xue-feng Zhang ; Institute of System Science, Northeastern University, Shenyang 110004, China ; Jin-kui Shang

The algorithm based on the particle swarm optimization adopted uniform distribution particles as the initial population combined with the rough entropy based on boundary region is presented, and it is applied to the image threshold segmentation. The algorithm adopts the rough entropy based on boundary region as the valuation standard of image segmentation and converses image segmentation problem into an optimization problem and has fully utilized particle swarm optimization function in the field of optimizing. The algorithm is realized with MATLAB programs. It is shown in experiments that not only the quality but also the stability of image segmentation is high, and the sensibility of the algorithm to the partition-size image sub-piece is low.

Published in:

2009 Chinese Control and Decision Conference

Date of Conference:

17-19 June 2009