Image segmentation algorithm based on dynamic particle swarm optimization and K-means clustering

ABSTRACT

In order to solve excessive independence of image segmentation quality of K-means clustering algorithm on initial clustering center for selection, and easily falling into the local optimal solution etc., one kind of image segmentation algorithm, dynamic particle swarm optimization and K-means (DPSOK) based on dynamic particle swarm optimization (DPSO) and K-means clustering was proposed in the Thesis. The performance of PSO algorithm was strengthened by dynamically adjusting inertia coefficient and learning factor; then fitness variance of particle swarm was calculated, and opportunity to transfer to K-means algorithm was found accurately; then K-means clustering center was initialized by utilizing DPSO output result to make it converge to the global optimal solution. Finally, K-means clustering center was continuously updated by minimizing multiple iterations of the target function until convergence. It is shown in the experimental result that DPSOK can effectively improve the global search capacity of K-means, and it has better segmentation effect compared with K-means and PSO in image segmentation. Compared with particle swarm optimization and K-means (PSOK) algorithm, DPSOK algorithm in the Thesis has higher segmentation quality and efficiency.

KEYWORDS:

• Image segmentation
• dynamic particle swarm optimization
• K-means clustering
• fitness variance
• clustering algorithm

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Jiangxi University of Science and Technology [20151BBF6-0071].

Notes on contributors

Wei Xiaoqiong

Wei Xiaoqiong has been associated with College of Music and Movies in Tianjin Normal University, Tiajin, China. He is interested in music for several years and published few articles related to his field. He is interested to spread music via the research work.

Yin E. Zhang

Yin E. Zhang is working with the Department of Computer and Mathematic in Gannan Normal University, China. He has been guiding novel research in different areas. He has published several research papers in multidisciplinary areas.