Multiple Smoothing and Morphological Techniques in Radiographic Image Enhancement

2011 ◽  
pp. 97-102
Keyword(s):  
Image Enhancement ◽  
Radiographic Image ◽  
Radiographic Image Enhancement

Multi-step radiographic image enhancement conforming to weld defect segmentation

2015 ◽  
Vol 9 (11) ◽  
pp. 943-950 ◽  
Author(s):  
Changying Dang ◽  
Yulin Xiao ◽  
Jianmin Gao ◽  
Zhao Wang ◽  
Fumin Chen
Keyword(s):  
Image Enhancement ◽  
Radiographic Image ◽  
Radiographic Image Enhancement ◽  
Weld Defect

scholarly journals Defect Inspection Based on Segmentation and Defective Tracking in Radiographic Image

2019 ◽  
Vol 8 (4) ◽  
pp. 11228-11236
Keyword(s):  
Orthogonal Polynomials ◽  
Image Enhancement ◽  
Radiographic Image ◽  
Edge Image ◽  
Radiographic Image Enhancement ◽  
Radiographic Images ◽  
Defect Identification ◽  
Enhancement Technique ◽  
Estimation Scheme ◽  
The Masses

In this paper, automatic weld defect segmentation into the radiographic image non-destructive evaluation and testing, with orthogonal polynomials transformation-enhancement (OPT-E) is presented. This proposed system defect identification the given defect Radiographic image. In digital radiographic images, the unknown masses appear very light with weak edges, and hence image enhancement technique needs to be applied with transform domain and radiographic images of some illustrative weld deserts invent. The proposed scheme has three phases. In first phase, a radiographic image enhancement technique, which is performed by logarithmic common variance and enhancement factor, computed from the absolute value of the orthogonal polynomials transformation coefficient as principal parameters for increasing the energy of the masses in the digital radiographic image enhancement. In case of successful enhanced of image in addition to gradient estimation scheme is working to point the edges current, in the next phase. The consequential edge image is again applied with orthogonal polynomials. In the final phase, edge tracking are the salient features with angle based defect identification. Experimental is improved quality of images and high relative segmentation by OPT-E.

RADIOGRAPHIC IMAGE ENHANCEMENT USING HYBRID ALGORITHM

2016 ◽  
Vol 78 (6-7) ◽  
Author(s):  
Varin Chouvatut ◽  
Ekkarat Boonchieng
Keyword(s):  
Image Quality ◽  
Spatial Resolution ◽  
Computed Radiography ◽  
Median Filter ◽  
Correct Diagnosis ◽  
Image Contrast ◽  
Radiographic Image ◽  
Radiographic Image Enhancement ◽  
Radiographic Images ◽  
Low Contrast

Radiographic image quality is important in the medical field since it can increase the visibility of anatomical structures and even improve the medical diagnosis. Because the image quality depends on contrast, noise, and spatial resolution, images with low contrast, a lot of noises, or low resolution will decrease image quality, leading to an incorrect diagnosis. Therefore, radiographic images should be enhanced to facilitate medical expertise in making correct diagnosis. In this paper, radiographic images are enhanced by hybrid algorithms based on the idea of combining three image processing techniques: Contrast Limited Adaptive Histogram Equalization for enhancing image contrast, Median Filter for removing noises, and Unsharp Masking for increasing spatial resolution. Two series of medical images consisting of 20 x-ray images and 20 computed radiography images are enhanced with this method. Peak Signal to Noise Ratio (PSNR) and image contrast are computed in order to measure image quality. The results indicate that the enhanced images have better PSNR.

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. 

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