Extraction of weld defect from radiographic images using the level set segmentation without re-initialization

2013 ◽  
Author(s):  
N. Ramou ◽  
M. Halimi
Keyword(s):  
Level Set ◽  
Radiographic Images ◽  
Level Set Segmentation ◽  
Weld Defect

scholarly journals Weld Inspection Based on Radiography Image Segmentation with Level Set Active Contour Guided Off-Center Saliency Map

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Mohamed Ben Gharsallah ◽  
Ezzeddine Ben Braiek
Keyword(s):  
Level Set ◽  
Defect Detection ◽  
Active Contour ◽  
Salient Feature ◽  
Saliency Map ◽  
Radiographic Images ◽  
Low Contrast ◽  
Small Defect ◽  
Weld Defect ◽  
Image Pixels

Radiography is one of the most used techniques in weld defect inspection. Weld defect detection becomes a complex task when uneven illumination and low contrast characterize radiographic images. In this paper we propose a new active contour based level set method for weld defect detection in radiography images. An off-center saliency map exploited as a feature to represent image pixels is embedded into a region energy minimization function to guide the level set active contour to defects boundaries. The aim behind using salient feature is that a small defect can frequently attract attention of human eyes which permits enhancing defects in low contrasted image. Experiment results on different weld radiographic images with various kinds of defects show robustness and good performance of the proposed approach comparing with other segmentation methods.

Retraction Notice: Improved Level Set Segmentation Algorithm Based on Kernel Fuzzy Particles Swarm Optimization (KFPSO) Clustering for MRI Images

2018 ◽  
Vol 14 ◽  
Author(s):  
G. Elaiyaraja
Keyword(s):  
Medical Imaging ◽  
Level Set ◽  
Current Medical ◽  
Segmentation Algorithm ◽  
Scientific Publishing ◽  
Swarm Optimization ◽  
Original Source ◽  
Level Set Segmentation ◽  
Copyright Violation ◽  
Retraction Notice

The article entitled “Improved Level Set Segmentation Algorithm Based on Kernel Fuzzy Particles Swarm Optimization (KFPSO) Clustering for MRI Images”, by G. Elaiyaraja, P. Epsiba, N. Kumaratharan and G. Suresh, has been retracted. Kindly see Bentham Science Policy on Article retraction at the link given below: (https://www.benthamscience.com/journals/current-medical-imaging/author-guidelines/). This article has been retracted on the request of the Editor. The authors have plagiarized a paper that had already been published in the journal Current Medical Imaging (CMIM) (Formerly: Current Medical Imaging Reviews) 14(3), Page: 389-400. http://www.eurekaselect.com/149444. It is a pre-requisite for authors to declare explicitly that their work is original and has not been published elsewhere. Authors are advised to properly cite the original source to avoid plagiarism and copyright violation. As such this article represents a severe abuse of the scientific publishing system. Bentham Science Publishers takes a very strong view on this matter and apologizes to the readers of the journal for any inconvenience this may cause.

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