Unsupervised Segmentation of Satellite Images Based on Neural Network and Genetic Algorithm

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 309)


Segmentation is one of the important processes in image analysis to extract the necessary but hidden information in the image. The success of the image analysis is based on the outcome of the segmentation process. There are number of methods proposed for the segmentation of satellite images. Soft computing approaches such as fuzzy logic, neural networks, and genetic algorithm are most widely used for the segmentation of satellite images. But, every method has its own advantages and disadvantages. In this paper, a new approach based on the combination of genetic algorithm and feed forward neural network is proposed for the segmentation of satellite images. In this process, the genetic algorithm selects and feeds the fittest individual to the neural network. This feed forward network performs the segmentation. The computational cost is drastically reduced due to this cooperative and parallel approach. Experimental result illustrates the efficiency of the proposed approach.


Segmentation Clustering Image enhancement Genetic algorithm Neural network 


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Copyright information

© Springer India 2015

Authors and Affiliations

  • P. Ganesan
    • 1
  • V. Rajini
    • 2
  • B.S. Sathish
    • 1
  • V. Kalist
    • 1
  1. 1.Department of Electronics and Control EngineeringSathyabama UniversityChennaiIndia
  2. 2.Department of Electrical and Electronics EngineeringSSN College of EngineeringChennaiIndia

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