Fast Level Set Algorithm for Extraction and Evaluation of Weld Defects in Radiographic Images

2016 ◽  
pp. 51-68
Author(s):  
Yamina Boutiche
Keyword(s):  
Level Set ◽  
Radiographic Images ◽  
Weld Defects

scholarly journals A Deep Artificial Immune System to Detect Weld Defects in DWDI Radiographic Images of Petroleum Pipes

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 180947-180964 ◽  
Author(s):  
Celia Cristina Bojarczuk Fioravanti ◽  
Tania Mezzadri Centeno ◽  
Myriam Regattieri De Biase Da Silva Delgado
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Artificial Immune ◽  
Radiographic Images ◽  
Weld Defects

An automatic system of classification of weld defects in radiographic images

2009 ◽  
Vol 42 (5) ◽  
pp. 467-476 ◽  
Author(s):  
Rafael Vilar ◽  
Juan Zapata ◽  
Ramón Ruiz
Keyword(s):  
Automatic System ◽  
Radiographic Images ◽  
Weld Defects

An Effective Method for Defects Detection in Radiographic Images of Welds Based on Edge Detection and Morphology

2013 ◽  
Vol 290 ◽  
pp. 71-77
Author(s):  
Wen Ming Guo ◽  
Yan Qin Chen
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Detection Algorithm ◽  
Morphological Processing ◽  
Radiographic Images ◽  
X Ray ◽  
Weld Defects ◽  
Detection Algorithms ◽  
Detection Quality

In the current industrial production, as steel weld X-ray images are low contrasted and noisy, the efficiency and precision can’t be both ensured. This paper has studied three different edge detection algorithms and found the most suitable one to detect weld defects. Combined with this edge detection algorithm, we proposed a new weld defects detection method. This method uses defect features to find the defects in edge images with morphological processing. Compared to the traditional methods, the method has ensured detection quality of weld defects detection.

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.

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