Neural Computing and Applications

, Volume 31, Supplement 2, pp 865–876 | Cite as

Self-organizing neural networks for image segmentation based on multiphase active contour

  • M. Sridevi
  • C. MalaEmail author
Original Article


Image segmentation is a process of segregating foreground object from background object in an image. This paper proposes a method to perform image segmentation for the color and textured images with a two-step approach. In the first step, self-organizing neurons based on neural networks are used for clustering the input image, and in the second step, multiphase active contour model is used to get various segments of an image. The contours are initialized in the active contour model with the help of the self-organizing maps obtained as a result of first step. From the results, it is inferred that the proposed method provides better segmentation result for all types of images.


Active contour Segmentation Neural network Self-organizing map 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© The Natural Computing Applications Forum 2017

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringNational Institute of TechnologyTiruchirappalliIndia

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