Fuzzy region-based active contour driven by global and local fitting energy for image segmentation

2021 ◽  
Vol 100 ◽  
pp. 106982
Author(s):  
Jiangxiong Fang ◽  
Huaxiang Liu ◽  
Jun Liu ◽  
Haiying Zhou ◽  
Liting Zhang ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Active Contour ◽  
Global And Local ◽  
Fuzzy Region ◽  
Local Fitting

scholarly journals A hybrid level set model for image segmentation

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0251914
Author(s):  
Weiqin Chen ◽  
Changjiang Liu ◽  
Anup Basu ◽  
Bin Pan
Keyword(s):  
Image Segmentation ◽  
Active Contour ◽  
Active Contour Model ◽  
Initial Contour ◽  
Edge Information ◽  
Contour Evolution ◽  
Contour Models ◽  
Global And Local ◽  
Local Fitting ◽  
Local Image

Active contour models driven by local binary fitting energy can segment images with inhomogeneous intensity, while being prone to falling into a local minima. However, the segmentation result largely depends on the location of the initial contour. We propose an active contour model with global and local image information. The local information of the model is obtained by bilateral filters, which can also enhance the edge information while smoothing the image. The local fitting centers are calculated before the contour evolution, which can alleviate the iterative process and achieve fast image segmentation. The global information of the model is obtained by simplifying the C-V model, which can assist contour evolution, thereby increasing accuracy. Experimental results show that our algorithm is insensitive to the initial contour position, and has higher precision and speed.

An Improved Image Segmentation Active Contour Model

2014 ◽  
Vol 513-517 ◽  
pp. 3463-3467
Author(s):  
Li Fen Zhou ◽  
Chang Xu Cai
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Image Segmentation ◽  
Active Contour ◽  
Active Contour Model ◽  
Local Region ◽  
Intensity Inhomogeneity ◽  
Contour Model ◽  
Global And Local ◽  
Region Information

The Chan-Vese (C-V) active contour model has low computational complexity, initialization and insensitive to noise advantagesand utilizes global region information of images, so it is difficult to handle images with intensity inhomogeneity. The Local binary fitting (LBF) model based on local region information has its certain advantages in mages segmentation of weak boundary or uneven greay.but , the segmentation results are very sensitive to the initial contours, In order to address this problem, this paper proposes a new active contour model with a partial differential equation, which integrates both global and local region information. Experimental results show that it has a distinctive advantage over C-V model for images with intensity inhomogeneity, and it is more efficient than LBF.

scholarly journals Fuzzy Region-Based Active Contours Driven by Weighting Global and Local Fitting Energy

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 184518-184536 ◽  
Author(s):  
Jiangxiong Fang ◽  
Huaxiang Liu ◽  
Liting Zhang ◽  
Jun Liu ◽  
Hesheng Liu
Keyword(s):  
Active Contours ◽  
Global And Local ◽  
Fuzzy Region ◽  
Local Fitting

scholarly journals Localized Patch-Based Fuzzy Active Contours for Image Segmentation

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Jiangxiong Fang ◽  
Hesheng Liu ◽  
Huaxiang Liu ◽  
Liting Zhang ◽  
Jun Liu
Keyword(s):  
Image Segmentation ◽  
Active Contour ◽  
Active Contours ◽  
Active Contour Model ◽  
Direct Method ◽  
Lagrange Equation ◽  
Energy Functional ◽  
Local Patch ◽  
A Direct Method ◽  
Fuzzy Region

This paper presents a novel fuzzy region-based active contour model for image segmentation. By incorporating local patch-energy functional along each pixel of the evolving curve into the fuzziness of the energy, we construct a patch-based energy function without the regurgitation term. Its purpose is not only to make the active contour evolve very stably without the periodical initialization during the evolution but also to reduce the effect of noise. In particular, in order to reject local minimal of the energy functional, we utilize a direct method to calculate the energy alterations instead of solving the Euler-Lagrange equation of the underlying problem. Compared with other fuzzy active contour models, experimental results on synthetic and real images show the advantages of the proposed method in terms of computational efficiency and accuracy.

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