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Multimedia Tools and Applications

, Volume 78, Issue 24, pp 35263–35287 | Cite as

Image segmentation using fuzzy competitive learning based counter propagation network

  • Siddharth Singh ChouhanEmail author
  • Ajay Kaul
  • Uday Pratap Singh
Article
  • 62 Downloads

Abstract

Image segmentation is the method of partitioning an image into some homogenous regions that are more meaningful for its better understanding and examination. Soft computing methods having the capabilities of achieving artificial intelligence are predominately used to perform the task of segmentation. Due to the variability and the uncertainty present in natural scenes, segmentation is a complicated task to perform with the help of conventional image segmentation techniques. Therefore, in this article a hybrid Fuzzy Competitive Learning based Counter Propagation Network (FCPN) is proposed for the segmentation of natural scene images. This method compromises of the uncertainty handling capabilities of the fuzzy system and proficiency of parallel learning ability of neural network. To identify the number of clusters automatically in less computational time, the instar layer of Counter propagation network (CPN) has been trained by using Fuzzy competitive learning (FCL). The outstar layer of counter propagation network is trained by using Grossberg learning for obtaining the desired output. Region growing method having the tendency to correctly identify edges with simplicity is used for initial seed point selection. Then, the most similar regions in the image are clustered and the number of clusters is estimated automatically. Finally, by identifying the cluster centers the images are segmented. Bacterial foraging algorithm is used to initialize the initial weights to the network, which helps the proposed method in achieving low convergence ratio with higher accuracy. Results validated the higher performance of proposed FCPN method when compared with other states-of-the-art methods. For future work, some other adaptive methods like the fuzzy model-based network can be used to identify multiple object regions and classifying them among separate clusters.

Keywords

Bacterial foraging algorithm Counter propagation network Fuzzy competitive learning Image segmentation Soft computing 

Notes

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Siddharth Singh Chouhan
    • 1
    Email author
  • Ajay Kaul
    • 1
  • Uday Pratap Singh
    • 2
  1. 1.School of Computer Science & EngineeringShri Mata Vaishno Devi UniversityKatraIndia
  2. 2.School of MathematicsShri Mata Vaishno Devi UniversityKatraIndia

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