Statistically Inhomogeneity Correction and Image Segmentation using Active Contours

Brijesh N Shah   and Jaymin K Bhalani

doi:10.17485/ijst/2017/v10i5/106604

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Statistically Inhomogeneity Correction and Image Segmentation using Active Contours

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2017/v10i5/106604

Year: 2017, Volume: 10, Issue: 5, Pages: 1-6

Original Article

Statistically Inhomogeneity Correction and Image Segmentation using Active Contours

Brijesh N Shah¹ and Jaymin K Bhalani²

¹Department of Electronics and Communication Engineering, C S Patel Institute of Technology, Charotar University of Science and Technology, Changa − 388421, Gujarat, India; [email protected] ²Department of Electronics and Communication Engineering, Babaria Institute of Technology, Varnama, Vadodara − 391240, Gujarat, India; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Objective: To improve results on noisy image. Method: We have proposed Gaussian distribution density function based inhomogeneity correction method with active contour. We have implemented proposed method in MATLAB. Findings: It is shown through stimulated results that the noise and inhomogeneity both are reduced in segmented images. Experimental work is carried out for gray scale images only and it is proven that noise has been significantly reduced for different gray scale images. Applications: Proposed method can be applied for the segmentation and analysis of the various images.

Keywords: Active Contour, Gaussian Distribution, Gray Scale Image, Inhomogeneity, Segmentation