Hybrid Active Contour Based on Local and Global Statistics Parameterized by Weight Coefficients for Inhomogeneous Image Segmentation

Hybrid Active Contour Based on Local and Global Statistics Parameterized by Weight Coefficients for Inhomogeneous Image Segmentation

Image inhomogeneity often occurs in real-world images and may present considerable difficulties during image segmentation. Therefore, this paper presents a new approach for the segmentation of inhomogeneous images. The proposed hybrid active contour model is formulated by combining the statistical i...

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Bibliographic Details
Main Authors: Asim Niaz, Kaynat Rana, Aditi Joshi, Asad Munir, Daeun Dana Kim, Hyun Chul Song, Kwang Nam Choi
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Active contours
bias field
image segmentation
intensity inhomogeneity
level set
Online Access:https://ieeexplore.ieee.org/document/9044368/

Internet

https://ieeexplore.ieee.org/document/9044368/

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