Joint Image Bias Field Correction and Segmentation

Sara Khurshid; Muhammad Salim Khan; Haider Ali; Awal Sher; Gohar Ayub Khan

Author(s)

Sara Khurshid Department of Mathematics, University of Peshawar, Pakistan

Muhammad Salim Khan Department of Mathematical Sciences University of Lakki Marwat, Khyber Pakhtunkhwa Pakistan

Haider Ali Department of Mathematics, University of Peshawar, Pakistan

Awal Sher Department of Mathematics, University of Peshawar, Pakistan

Gohar Ayub Khan Department of Mathematical Sciences University of Lakki Marwat, Khyber Pakhtunkhwa Pakistan

Abstract

It is a well-known fact that in modern technology, digital images play a vital role. Image processing is used in order to accurately use these images. The main purpose of image segmentation is to separate a particular image into regions or objects that are meaningful. But image segmentation becomes very challenging when there is intensity inhomogeneity or bias field in the given image's. Several models have been proposed in order to perform accurate segmentation but still there are issues. For this purpose we design a novel model for efficiently segmenting and bias field correction. Experimental results on medical, out-door and synthetic images validate the performance of the proposed model in contrast with the existing models.

Publication Details

Page(s) 24-40

DOI DOI not available

Published Journal: The Sciencetech, Volume: 3, Issue: 2, Year: 2022

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Keywords

Bias Field Correction, Level Set Method, Calculus of Variations, image segmentation, Partial Differential Equations

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