• DocumentCode
    596651
  • Title

    A new image segmentation hybrid algorithm

  • Author

    Yongfeng Xu ; Bo Zhang ; Yongli Su

  • Author_Institution
    Dept. of Mathematic, Northwest Univ., Xi´´an, China
  • fYear
    2012
  • fDate
    18-20 Oct. 2012
  • Firstpage
    587
  • Lastpage
    589
  • Abstract
    A new hybrid algorithm for image segmentation based on k-mean and particle swarm optimization algorithm is proposed in the paper. K-mean clustering algorithm is a local search algorithm because it is easily to be trapped in local optimum and is sensitive to initial value effectively. On the other hand, particle swarm optimization algorithm is a global optimization algorithm. Because of taking the criterion function of k-mean as the object function of PSO, this algorithm incorporates the local search ability of k-mean algorithm with the global optimization ability of PSO. Experiments show that the new algorithm can get the optimal quantizated image by PSNR and RMSE.
  • Keywords
    image segmentation; particle swarm optimisation; pattern clustering; search problems; PSNR; PSO; RMSE; global optimization algorithm; hybrid algorithm; image segmentation; k-mean clustering algorithm; local search ability; local search algorithm; object function; particle swarm optimization algorithm; Algorithm design and analysis; Clustering algorithms; Image segmentation; Optimization; Particle swarm optimization; Partitioning algorithms; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-1743-6
  • Type

    conf

  • DOI
    10.1109/ICACI.2012.6463233
  • Filename
    6463233