Non-referenced quality assessment of image processing methods in infrared non-destructive testing based on higher order statistics

2015 ◽  
Author(s):  
T.J. Ramirez-Rozo ◽  
J.C. Garcia-Alvarez
Keyword(s):  
Image Processing ◽  
Quality Assessment ◽  
Order Statistics ◽  
Higher Order ◽  
Higher Order Statistics ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Processing Methods ◽  
Non Destructive

Acoustic and Photoacoustic Inspection of Through-Silicon Vias in the GHz-Frequency Band

2017 ◽  
Author(s):  
Sebastian Brand ◽  
Michael Kögel ◽  
Frank Altmann ◽  
Ingrid DeWolf ◽  
Ahmad Khaled ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Frequency Band ◽  
Process Development ◽  
Three Dimensional ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Vertical Interconnection ◽  
Testing Techniques ◽  
Silicon Vias ◽  
Non Destructive

Abstract Through Silicon Via (TSV) is the most promising technology for vertical interconnection in novel three-dimensional chip architectures. Reliability and quality assessment necessary for process development and manufacturing require appropriate non-destructive testing techniques to detect cracks and delamination defects with sufficient penetration and imaging capabilities. The current paper presents the application of two acoustically based methods operating in the GHz-frequency band for the assessment of the integrity of TSV structures.

scholarly journals Defect Estimation in Non-Destructive Testing of Composites by Ultrasonic Guided Waves and Image Processing

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 315 ◽  
Author(s):  
Kumar Anubhav Tiwari ◽  
Renaldas Raisutis ◽  
Olgirdas Tumsys ◽  
Armantas Ostreika ◽  
Kestutis Jankauskas ◽  
...  
Keyword(s):  
Image Processing ◽  
Composite Structures ◽  
Guided Waves ◽  
Low Frequency ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Discrete Wavelet ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Non Destructive

The estimation of the size and location of defects in multi-layered composite structures by ultrasonic non-destructive testing using guided waves has attracted the attention of researchers for the last few decades. Although extensive signal processing techniques are available, there are only a few studies available based on image processing of the ultrasonic B-scan image to extract the size and location of defects via the process of ultrasonic non-destructive testing. This work presents an image processing technique for ultrasonic B-scan images to improve the estimation of the location and size of disbond-type defects in glass fiber-reinforced plastic materials with 25-mm and 51-mm diameters. The sample is a segment of a wind turbine blade with a variable thickness ranging from 3 to 24 mm. The experiment is performed by using a low-frequency ultrasonic system and a pair of contact-type piezoceramic transducers kept apart by a 50-mm distance and embedded on a moving mechanical panel. The B-scan image acquired by the ultrasonic pitch-catch technique is denoised by utilizing features of two-dimensional discrete wavelet transform. Thereafter, the normalized pixel densities are compared along the scanned distance on the region of interest of the image, and a −3 dB threshold is applied to the locations and sizes the defects in the spatial domain.

scholarly journals Evaluating the performance of various segmentation techniques in industrial radiographs

2014 ◽  
Vol 14 (1) ◽  
pp. 161-171
Author(s):  
Mythili Thirugnanam ◽  
S. Margret Anouncia
Keyword(s):  
Image Processing ◽  
Region Of Interest ◽  
Non Destructive Testing ◽  
Gray Scale ◽  
Destructive Testing ◽  
Radiographic Images ◽  
Segmentation Algorithms ◽  
Industrial Inspection ◽  
Pros And Cons ◽  
Non Destructive

Abstract At present, image processing concepts are widely used in different fields, such as remote sensing, communication, medical imaging, forensics and industrial inspection. Image segmentation is one of the key processes in image processing key stages. Segmentation is a process of extracting various features of the image which can be merged or split to build the object of interest, on which image analysis and interpretation can be performed. Many researchers have proposed various segmentation algorithms to extract the region of interest from an image in various domains. Each segmentation algorithm has its own pros and cons based on the nature of the image and its quality. Especially, extracting a region of interest from a gray scale image is incredibly complex compared to colour images. This paper attempts to perform a study of various widely used segmentation techniques in gray scale images, mostly in industrial radiographic images that would help the process of defects detection in non-destructive testing.

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