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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 9
2856-2860

Multi-level threshold image segmentation algorithm based on particle swarm optimization and fuzzy entropy

Lyu Fuqi1
Li Xiaomin2
1. Dept. of Basic Course Teaching, Rongzhi College of Chongqing Technology & Business University, Chongqing 401320, China
2. College of Mathematics & Statistics, Chongqing Technology & Business University, Chongqing 400067, China
DOI: 10.19734/j.issn.1001-3695.2018.04.0236

Abstract

Aiming at the problem that the existing threshold segmentation algorithm uses the exhaustive search to find the optimal threshold and the calculation cost is relatively large, this paper proposed a multi-level threshold image segmentation algorithm based on particle swarm optimization and fuzzy entropy. Image segmentation was a very important preprocessing step in image analysis. In the proposed method, it first selected Shannon entropy and fuzzy entropy as the objective function of the optimization technique. Then it established a multi-level image threshold segmentation based on particle swarm optimization algorithm, and performed image segmentation by maximizing Shannon entropy or fuzzy entropy. Finally, it selected Lena, baboon and airplane from the image segmentation database as test images for performance analysis(including robustness, efficiency and convergence), and compared with several existing threshold segmentation algorithms. The results show that the proposed algorithm obtains higher PSNR value and less classification error, which proves that this algorithm is an efficient multi-level threshold image segmentation algorithm.

Foundation Support

国家自然科学基金资助项目(61402063)
重庆市基础与前沿一般项目(CSTC2014JCYJA00033)
重庆市教委科技项目(KJ1400630)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.04.0236
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 9
Section: Technology of Graphic & Image
Pages: 2856-2860
Serial Number: 1001-3695(2019)09-064-2856-05

Publish History

[2019-09-05] Printed Article

Cite This Article

吕福起, 李霄民. 基于粒子群优化算法和模糊熵的多级阈值图像分割算法 [J]. 计算机应用研究, 2019, 36 (9): 2856-2860. (Lyu Fuqi, Li Xiaomin. Multi-level threshold image segmentation algorithm based on particle swarm optimization and fuzzy entropy [J]. Application Research of Computers, 2019, 36 (9): 2856-2860. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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