Variational level set image segmentation model coupled with kernel distance function. (June 2020)

• Record Type: Journal Article
• Authors: Badshah, Noor; Ahmad, Ali; Rehman, Fazli
• Is Part Of: Journal of algorithms & computational technology. Volume 14(2020)
• Publication Date: 2020-06
• Subjects: Image segmentation -- level set -- kernel function -- kernel tricks -- functional minimization -- Euler's Lagrange equation -- finite difference method; Computer algorithms -- Periodicals; Numerical calculations -- Periodicals; Computer algorithms; Numerical calculations; Periodicals; 518.1
• DOI: 10.1177/1748302620931421
• Languages: English
• ISSNs: 1748-3018

Abstract

One of the crucial challenges in the area of image segmentation is intensity inhomogeneity. For most of the region-based models, it is not easy to completely segment images having severe intensity inhomogeneity and complex structure, as they rely on intensity distributions. In this work, we proposed a firsthand hybrid model by blending kernel and Euclidean distance metrics. Experimental results on some real and synthetic images suggest that our proposed model is better than models of Chan and Vese, Wu and He, and Salah et al.