Improved Color Image Segmentation using Kindred Thresholding and Region Merging

Authors

  • Giridhar S Sudi Dept. of E&C , Gogte Institute of Technology, Belgaum, Karnataka, India
  • Aashish A Gadgil Dept. of E&C , Gogte Institute of Technology, Belgaum, Karnataka, India

Keywords:

Color Image Segmentation, Fuzzy Logic, Region Merge, Color Space, Thresholding

Abstract

In this paper, a color image segmentation approach based on holographic thresholding and region merging is presented. The holographic image considers both the occurrence of the gray levels and the neighboring nearest value among-st pixels. Thus, it employs both the local and global information. Holographic analysis is performed using fuzzy entropy as a tool for finding all major kindred regions at the first stage followed by region merging process which is carried out based on color similarity among-st these regions to avoid over segmentation. The proposed Kindred -based approach (KOB) is compared with the histogram-based approach (HIB). The experimental results demonstrate that the KOB can find similar regions more effectively than HIB does, and thus can solve the problem of discriminating shading in color images to a greater extent.

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Published

2013-11-30

How to Cite

[1]
G. S. Sudi and A. A. Gadgil, “Improved Color Image Segmentation using Kindred Thresholding and Region Merging”, Int. J. Comp. Sci. Eng., vol. 1, no. 3, pp. 1–9, Nov. 2013.

Issue

Vol. 1 No. 3 (2013): IJCSE November Edition

Section

Research Article

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