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Multi-threshold Image Segmentation Through an Improved Quantum-Behaved Particle Swarm Optimization Algorithm

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Cloud Computing and Security (ICCCS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9483))

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Abstract

Multi-threshold segmentation is a basic and widely used technique in image segmentation. The key step of accomplishing this task is to find the optimal multi-threshold value, which in essence can be reduced to multi-objective optimization problem. The quantum particle-behaved swarm algorithm (QPSO) is an effective method to resolve the problem of this class. However in practice, we found the original QPSO has imperfections, such as the excessive dropping of the diversity of the population and trapping in local optimum. In order to improve the ability of searching the global optimum and accelerate the speed of convergence, we proposed an improved quantum-behaved particle swarm algorithm (IQPSO). The experiments showed that IQPSO was superior to PSO and QPSO on the searching of multi-threshold value in image segmentation under the premise of ensuring the accuracy of solutions.

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Acknowledgments

This work is supported by the open fund of the key laboratory in Southeast University of computer network and information integration of the ministry of education (Grant No. K93-9-2015-10C).

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Authors and Affiliations

  1. School of Computer Science, Anhui University of Technology, Maanshan, 243005, China

    Wang Jiali, Liu Hongshen & Ruan Yue

  2. School of Computer Science and Engineering, Southeast University, Nanjing, 210096, China

    Ruan Yue

  3. Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing, 210096, China

    Ruan Yue

Authors
  1. Wang Jiali
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  2. Liu Hongshen
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  3. Ruan Yue
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Corresponding author

Correspondence to Wang Jiali .

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Editors and Affiliations

  1. Nanjing University of Aeronautics and As, Nanjing, China

    Zhiqiu Huang

  2. Nanjing University of Information Scienc, Nanjing, China

    Xingming Sun

  3. Nanjing, China

    Junzhou Luo

  4. Nanjing University of Aeronautics and As, Nanjing, China

    Jian Wang

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Jiali, W., Hongshen, L., Yue, R. (2015). Multi-threshold Image Segmentation Through an Improved Quantum-Behaved Particle Swarm Optimization Algorithm. In: Huang, Z., Sun, X., Luo, J., Wang, J. (eds) Cloud Computing and Security. ICCCS 2015. Lecture Notes in Computer Science(), vol 9483. Springer, Cham. https://doi.org/10.1007/978-3-319-27051-7_10

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  • DOI: https://doi.org/10.1007/978-3-319-27051-7_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27050-0

  • Online ISBN: 978-3-319-27051-7

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