Three-dimensional mapping of non-complex specimens by image processing and optical density evaluation of digitised radiographs

Rokrok, B.; Edalati, Kaveh; Yahaghi, Effat; Mohammadzadeh, Noureddin; Rastkhah, N.; Amir, Mohammad

doi:10.1784/insi.2009.51.6.315

Cited by 2 publications

(3 citation statements)

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“…In the radiography test method, images are often very noisy, have low contrast, and need to be processed [1][2][3]6]. The radiographic images from some objects were provided according to Sect.…”

Section: Resultsmentioning

confidence: 99%

“…New developments are constantly modifying the radiographic techniques applied, thereby producing technical or economic advantages, or both, over previous techniques [1][2][3][4]. Special techniques such as digital radiography, image analysis and image enhancement are used to improve the quality of radiography images for better interpretation.…”

Section: Introductionmentioning

confidence: 99%

“…Special techniques such as digital radiography, image analysis and image enhancement are used to improve the quality of radiography images for better interpretation. Problems such as the presence of noise and insufficient contrast are frequently found on conventional radiographs, and other methods of processing are required to reveal the defects [3,5]. Correct inspection of radiographs will depend essentially on the image quality and the interpreter's experience in his evaluation.…”

Section: Introductionmentioning

confidence: 99%

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Defect Detection Improvement of Digitised Radiographs by Principal Component Analysis with Local Pixel Grouping

2015

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Radiographic inspection is one of the most important techniques among non-destructive testing methods. Radiographic images are often very noisy and the image quality and the interpreter's experience can affect the inspection of radiographs and their evaluation. In this research, principal component analysis (PCA) with local pixel grouping (LPG) algorithms was used for image enhancement for radiograph image interpretation. In this method, a pixel and its neighbors are considered as a vector variable for preservation of radiography image local structure. This method is a statistical method that uses an orthogonal property to transform and convert a set of observations of possibly correlated variables into a set of values of uncorrelated variables. Here, the PCA-LPG denoising algorithm has been applied to radiographic images with different defects to obtain denoised images. The results show that the contrast of denoised radiography images is better than the original image and the defects are much clearer. Also, the evaluation of the image quality enhancement show the contrast to noise level increases almost two times by the proposed PCA-LPG method.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Defect Detection Improvement of Digitised Radiographs by Principal Component Analysis with Local Pixel Grouping

2015

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Research on a DS-class X-ray film digitisation device and an image enhancement algorithm with 12-bit RAW data

Wang

et al. 2023

insight

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Automatic evaluation of the X-ray films of welds is an important area of study in the field of non-destructive testing (NDT). A digitising device for the X-ray film is the key to realising automatic evaluation and its image quality directly determines the quality of the automatic evaluation system. At present, the imaging quality of most mature digitising systems on the market cannot meet the DS-class requirements of international standard EN 14096. In order to solve the problems of low visual contrast, detailed information that is difficult to distinguish and low visual resolution in existing digitising systems, a high-quality embedded X-ray film digitising device, processing films with adjustable width, is developed in this paper. The device uses a 12-bit camera and has the characteristics of small size, simple operation and easy maintenance. In order to improve the imaging quality, an optical visual enhancement model is constructed for the generated 12-bit RAW data, which can improve the display of the data. The MTF20% values of the device in the horizontal and vertical directions are 7.544 and 7.460, respectively, and the optical density range is 0.5-4.5 D, the comprehensive index of which can reach DS class. The device has been initially applied by non-destructive testing companies.

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Three-dimensional mapping of non-complex specimens by image processing and optical density evaluation of digitised radiographs

Cited by 2 publications

References 10 publications

Defect Detection Improvement of Digitised Radiographs by Principal Component Analysis with Local Pixel Grouping

Defect Detection Improvement of Digitised Radiographs by Principal Component Analysis with Local Pixel Grouping

Research on a DS-class X-ray film digitisation device and an image enhancement algorithm with 12-bit RAW data

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