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.

Digital Radiographic Image Enhancement for Weld Defect Detection using Smoothing and Morphological Transformations

2012 ◽  
Vol 9 (1) ◽  
pp. 15
Author(s):  
Suhaila Abdul Halim ◽  
Arsmah Ibrahim ◽  
Yupiter Harangan Prasada Manurung
Keyword(s):  
Defect Detection ◽  
Test Method ◽  
Radiographic Image ◽  
Radiographic Image Enhancement ◽  
Radiographic Images ◽  
Weld Defect ◽  
Different Types ◽  
Morphological Transformations ◽  
Non Destructive

Accurate inspection of welded materials is important in relation to achieve acceptable standards. Radiography, a non-destructive test method, is commonly used to evaluate the internal condition of a material with respect to defect detection. The presence of noise in low resolution of radiographic images significantly complicates analysis; therefore attaining higher quality radiographic images makes defect detection more readily achievable. This paper presents a study pertaining to the quality enhancement of radiographic images with respect to different types of defects. A series of digital radiographic weld flaw images were smoothed using multiple smoothing techniques to remove inherent noise followed by top and bottom hat morphological transformations. Image quality was evaluated quantitatively with respect to SNR, PSNR and MAE. The results indicate that smoothing enhances the quality of radiographic images, thereby promoting defect detection with the respect to original radiographic images. 

Digital Radiographic Image Enhancement for Weld Defect Detection using Smoothing and Morphological Transformations

2012 ◽  
Vol 9 (1) ◽  
pp. 15
Author(s):  
Suhaila Abdul Halim ◽  
Arsmah Ibrahim ◽  
Yupiter Harangan Prasada Manurung
Keyword(s):  
Defect Detection ◽  
Test Method ◽  
Radiographic Image ◽  
Radiographic Image Enhancement ◽  
Radiographic Images ◽  
Weld Defect ◽  
Internal Condition ◽  
Different Types ◽  
Morphological Transformations ◽  
Non Destructive

Accurate inspection ofweldedmaterials is important in relation to achieve acceptable standards. Radiography, a non-destructive test method, is commonly used to evaluate the internal condition ofa material with respect to defect detection. Thepresence ofnoise in low resolution ofradiographic images significantly complicates analysis; thereforeattaining higher quality radiographic images makes defect detection more readily achievable. This paper presents a study pertaining to the quality enhancement of radiographic images with respect to different types of defects. A series of digital radiographic weld flaw images were smoothed using multiple smoothing techniques to remove inherent noise followed by top and bottom hat morphological transformations. Image quality was evaluated quantitatively with respect to SNR, PSNR andMAE. The results indicate that smoothing enhances the quality ofradiographic images, thereby promoting defect detection with the respect to original radiographic images.

Weld defect detection on digital radiographic image using level set method

2013 ◽  
Author(s):  
Suhaila Abd Halim ◽  
Bertha Trissan Petrus ◽  
Arsmah Ibrahim ◽  
Yupiter HP Manurung ◽  
Mohd Idris Jayes
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Defect Detection ◽  
Radiographic Image ◽  
Weld Defect

DWT Based Automated Weld Pool Detection and Defect Characterisation from Weld Radiographs

2014 ◽  
Vol 984-985 ◽  
pp. 573-578 ◽  
Author(s):  
K. Sudheera ◽  
N.M. Nandhitha ◽  
Lakshmi Mohanachandran ◽  
Parithosh Nanekar ◽  
B. Venkatraman ◽  
...  
Keyword(s):  
Defect Detection ◽  
Indirect Method ◽  
Detection System ◽  
Defect Region ◽  
Low Contrast ◽  
Domain Specific ◽  
Industrial Radiography ◽  
Considerable Research ◽  
Weld Defect ◽  
Defect Characterisation

Industrial Radiography is the most widely accepted NDT technique for weld quality in industries. As it is an indirect method, defect type and nature must be obtained by analyzing the radiographs. Manual interpretation of radiographs is subjective in nature. So the paradigm shifted to automated weld defect detection system. Though considerable research is done in automated weld defect detection, an accurate domain specific technique has not yet been evolved due to noise, artifacts in radiographs, low contrast between the defect region and the background and difficulty in isolating the defect. The proposed work aims at developing an automated weld defect detection system that enhances the contrast between the object and the background and isolates the weld defect. In this work, real time weld radiographs are acquired and contrast enhancement is performed with DWT. Slag and Porosity are isolated and dimensionally characterized.

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