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

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Abstract

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.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Tiruchirappalli, 620 015, India

    M. Sridevi & C. Mala

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  1. M. Sridevi
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  2. C. Mala
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Correspondence to C. Mala.

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Sridevi, M., Mala, C. Self-organizing neural networks for image segmentation based on multiphase active contour. Neural Comput & Applic 31 (Suppl 2), 865–876 (2019). https://doi.org/10.1007/s00521-017-3045-1

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