UGC Approved Journal no 63975(19)

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Published in:

Volume 6 Issue 5
May-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR1905918


Registration ID:
211208

Page Number

85-90

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Title

Bias Correction and Segmentation of Images with Intensity Inhomogeneity

Abstract

Intensity non-uniformity or intensity inhomogeneity usually occurs in Real world Images, those images cannot be segmented by using image segmentation. The most commonly used algorithms in image segmentation are region based and depends on the homogeneity of the image intensities which usually fails to produce accurate segmentation results due to the intensity non-uniformity. In this paper we proposed a novel region based method for image segmentation which can be able to discuss with intensity non-uniformities in image segmentation. First according to the image models with intensity non-uniformities we define a local clustering criterion function for the intensities in the image neighborhood of each part. The local clustering criterion function is then integrated with respect to the neighborhood center to give a global criterion of image segmentation. In a level set formulation this criterion defines an energy in terms of level set functions that represents the partition of image domain and a bias field that corresponds to the intensity non-uniformity of the image. Therefore, by minimizing the energy we can able to segment the image simultaneously and estimate the bias field can be used for the intensity non-uniformity correction. This method is applied on MRI images and real world images of various modalities with desirable performance in the presence of intensity non-uniformities. The experiment results show that the method is stronger, faster and more accurate than the well-known piecewise smooth model and gives promising results. As an application this method is used for segmentation and bias correction of real world images and MRI images with better results.

Key Words

Bias field, Energy minimization, Image segmentation, Intensity non-uniformity, Level set method

Cite This Article

"Bias Correction and Segmentation of Images with Intensity Inhomogeneity", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.85-90, May-2019, Available :http://www.jetir.org/papers/JETIR1905918.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Bias Correction and Segmentation of Images with Intensity Inhomogeneity", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp85-90, May-2019, Available at : http://www.jetir.org/papers/JETIR1905918.pdf

Publication Details

Published Paper ID: JETIR1905918
Registration ID: 211208
Published In: Volume 6 | Issue 5 | Year May-2019
DOI (Digital Object Identifier):
Page No: 85-90
Country: SPSR Nellore, Andhrapradesh, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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