A Review on Image Segmentation Using Different Optimization Techniques

Authors

  • S Pathak Department of CSE and IT, Madhav Institute of Technology and Science, Gwalior, India
  • V Sejwar Department of CSE and IT, Madhav Institute of Technology and Science, Gwalior, India

Keywords:

Image Segmentation, Edge Segmentation, Region Segmentation, Data Clustering, Genetic Algorithm

Abstract

Image segmentation is one of the most significant ways to simplify complex images into human or machine readable form. The main purpose of image segmentation is to extract or segment out particular area or region of image, so that that the analysis become easier regarding its shape, size, and its boundaries. It can also be used to separate foreground image from the background image. Image segmentation has its wide utility for medical image analysis, satellite images, as well in many other fields. Segmentation methods have been applied in various computer vision fields, such as scene interpretation and representation, content based image retrieval, object tracking in videos, medical applications etc. Here various segmentation methods and Optimization techniques are being discussed with their applications in various fields. The work done in the field of image segmentation using Swarm Optimization techniques like Genetic Algorithm, Particle Swarm Optimization, Fire-Fly and many more existing techniques are been discussed in this paper.

References

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Published

2025-11-11

How to Cite

[1]
S. Pathak and V. Sejwar, “A Review on Image Segmentation Using Different Optimization Techniques”, Int. J. Comp. Sci. Eng., vol. 5, no. 5, pp. 217–221, Nov. 2025.

Issue

Vol. 5 No. 5 (2017): IJCSE May Edition

Section

Review Article

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