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International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.9, No.2, Feb. 2017

The Image Segmentation Techniques

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Author(s)

Shiv Gehlot, John Deva Kumar

Index Terms

Image segmentation;normalized self correlation function;relative error function;piecewise image segmentation;Laplace filter;Otsu's method

Abstract

Image segmentation has a crucial role in image processing. Classical segmentation techniques based on thresholding have been extensively used but they fail drastically for noisy or non-uniformly illuminated images. Several alternatives presented over the time have filled this void but with increased complexity. In this paper we present an algorithm to address the above issues with minimum complexity. We propose normalized self correlation function (NSCF) which forms a basis for the progress of the algorithm. We also introduce relative error function (REF) which is used for qualitative assessment of the algorithm and its comparison with other algorithms. We also propose a second algorithm named piecewise image segmentation (PIS) which is a generalized edge-based method able to generate any desired edge map. The results show that the proposed algorithms are able to perform well for different scenarios and at the same time better than traditional algorithms. 

Cite This Paper

Shiv Gehlot, John Deva Kumar,"The Image Segmentation Techniques", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.9, No.2, pp.9-18, 2017.DOI: 10.5815/ijigsp.2017.02.02

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