Image Change Detection Using Particle Swarm Optimization

  • Santwana Sagnika
  • Saurabh Bilgaiyan
  • Bhabani Shankar Prasad Mishra
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 308)


Image change detection can be expressed as a function of time period, whose main objective is to find the changes on the same area at different time intervals, which is a complex and intractable one. Due to large search space, general optimization algorithm fails to give the solution in a promising amount of time. So particle swarm optimization (PSO), one of the swarm-based approaches, can be used as an efficient tool, which the authors have explored in this paper. This mechanism aims to find a change mask that performs partitioning of image into changed and unchanged areas so that the weighted sum of mean square errors of both areas is minimized. This leads to accurate change detection with less noise in a feasible time period.


Image processing Change detection PSO Difference image Mean square error 


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Copyright information

© Springer India 2015

Authors and Affiliations

  • Santwana Sagnika
    • 1
  • Saurabh Bilgaiyan
    • 1
  • Bhabani Shankar Prasad Mishra
    • 1
  1. 1.School of Computer EngineeringKIIT UniversityBhubaneswarIndia

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