ETVOS: An Enhanced Total Variation Optimization Segmentation Approach for SAR Sea-Ice Image Segmentation

2013 ◽  
Vol 51 (2) ◽  
pp. 925-934 ◽  
Author(s):  
Tae-Jung Kwon ◽  
Jonathan Li ◽  
Alexander Wong
Keyword(s):  
Image Segmentation ◽  
Sea Ice ◽  
Total Variation ◽  
Segmentation Approach

scholarly journals A NOVEL IMAGE SEGMENTATION APPROACH BASED ON NEUTROSOPHIC SET AND IMPROVED FUZZY C-MEANS ALGORITHM

2011 ◽  
Vol 07 (01) ◽  
pp. 155-171 ◽  
Author(s):  
H. D. CHENG ◽  
YANHUI GUO ◽  
YINGTAO ZHANG
Keyword(s):  
Image Segmentation ◽  
Point Of View ◽  
Neutrosophic Set ◽  
Convergence Criterion ◽  
Complex Objects ◽  
Fuzzy C Means ◽  
Segmentation Methods ◽  
Segmentation Algorithms ◽  
Segmentation Approach ◽  
Fuzzy C Means Algorithm

Image segmentation is an important component in image processing, pattern recognition and computer vision. Many segmentation algorithms have been proposed. However, segmentation methods for both noisy and noise-free images have not been studied in much detail. Neutrosophic set (NS), a part of neutrosophy theory, studies the origin, nature, and scope of neutralities, as well as their interaction with different ideational spectra. However, neutrosophic set needs to be specified and clarified from a technical point of view for a given application or field to demonstrate its usefulness. In this paper, we apply neutrosophic set and define some operations. Neutrosphic set is integrated with an improved fuzzy c-means method and employed for image segmentation. A new operation, α-mean operation, is proposed to reduce the set indeterminacy. An improved fuzzy c-means (IFCM) is proposed based on neutrosophic set. The computation of membership and the convergence criterion of clustering are redefined accordingly. We have conducted experiments on a variety of images. The experimental results demonstrate that the proposed approach can segment images accurately and effectively. Especially, it can segment the clean images and the images having different gray levels and complex objects, which is the most difficult task for image segmentation.

A Hybrid Image Segmentation Approach for Thermal Barrier Coating Quality Assessments

2021 ◽  
Author(s):  
Zanyah Ailsworth ◽  
Wei-Bang Chen ◽  
Yongjin Lu ◽  
Xiaoliang Wang ◽  
Melissa Tsui ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Thermal Barrier Coating ◽  
Thermal Barrier ◽  
Coating Quality ◽  
Barrier Coating ◽  
Segmentation Approach ◽  
Quality Assessments

scholarly journals An Image Segmentation Method Based on Improved Regularized Level Set Model

2018 ◽  
Vol 8 (12) ◽  
pp. 2393 ◽  
Author(s):  
Lin Sun ◽  
Xinchao Meng ◽  
Jiucheng Xu ◽  
Shiguang Zhang
Keyword(s):  
Image Segmentation ◽  
Level Set ◽  
Energy Functional ◽  
External Energy ◽  
Regularization Term ◽  
Level Set Function ◽  
New Energy ◽  
Segmentation Approach ◽  
Set Function ◽  
Distance Regularization

When the level set algorithm is used to segment an image, the level set function must be initialized periodically to ensure that it remains a signed distance function (SDF). To avoid this defect, an improved regularized level set method-based image segmentation approach is presented. First, a new potential function is defined and introduced to reconstruct a new distance regularization term to solve this issue of periodically initializing the level set function. Second, by combining the distance regularization term with the internal and external energy terms, a new energy functional is developed. Then, the process of the new energy functional evolution is derived by using the calculus of variations and the steepest descent approach, and a partial differential equation is designed. Finally, an improved regularized level set-based image segmentation (IRLS-IS) method is proposed. Numerical experimental results demonstrate that the IRLS-IS method is not only effective and robust to segment noise and intensity-inhomogeneous images but can also analyze complex medical images well.

Hybrid Image Segmentation Within a Computer Vision Hierarchy

1993 ◽  
Vol 30 (1) ◽  
pp. 51-64
Author(s):  
Ray Thomas ◽  
Fariborz Zahedi
Keyword(s):  
Computer Vision ◽  
Image Segmentation ◽  
Vision System ◽  
Critical Role ◽  
Generic Model ◽  
Test Results ◽  
Segmentation Approach ◽  
Edge Based

Hybrid image segmentation within a computer vision hierarchy A generic model of a computer vision system is presented which highlights the critical role of image segmentation. A hybrid segmentation approach, utilising both edge-based and region-based techniques, is proposed for improved quality of segmentation. An image segmentation architecture is outlined and test results are presented and discussed.

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