Variational level set image segmentation model coupled with kernel distance function
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...
Main Authors: | Noor Badshah, Ali Ahmad, Fazli Rehman |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2020-06-01
|
Series: | Journal of Algorithms & Computational Technology |
Online Access: | https://doi.org/10.1177/1748302620931421 |
Similar Items
-
Fast iterative methods for variational models in image segmentation
by: Badshah, Noor
Published: (2009) -
Fractional Distance Regularized Level Set Evolution With Its Application to Image Segmentation
by: Meng Li, et al.
Published: (2020-01-01) -
MRI Image Segmentation Using Conditional Spatial FCM Based on Kernel-Induced Distance Measure
by: B. Gharnali, et al.
Published: (2018-06-01) -
A Variational Level Set Model Combined with FCMS for Image Clustering Segmentation
by: Liming Tang
Published: (2014-01-01) -
Modified Kernel Functions by Geodesic Distance
by: Yong Quan, et al.
Published: (2004-01-01)