Naslov
Rapid Defect Detection by Merging Ultrasound B- scans from Different Scanning Angles

Autori
Medak, Duje ; Posilovic, Luka ; Subasic, Marko ; Petkovic, Tomislav ; Budimir, Marko ; Loncaric, Sven

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) / - : Institute of Electrical and Electronics Engineers (IEEE), 2021, 219-224

Skup
12th International Symposium on Image and Signal Processing and Analysis (ISPA 2021)

Mjesto i datum
Zagreb, Hrvatska, 13.09.2021. - 15.09.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
image processing ; image analysis ; convolutional neural networks ; ultrasonic imaging ; nondestructive testing ; automated flaw detection

Sažetak
Ultrasonic testing (UT) is a commonly used approach for inspection of material and defect detection without causing harm to the inspected component. To improve the reliability of defect detection, the material is often scanned from various angles leading to an immense amount of data that needs to be analyzed. Some of the defects are only seen on B-scans taken from a particular angle so discarding some of the data would increase the risk of not detecting all of the defects. Recently there has been significant progress in the development of methods for automated defect analysis from the UT data. Using such methods the inspection can be performed quicker, but it is still necessary to inspect all of the angles to detect defects. In this work, we test a novel approach for accelerating the analysis by merging the images from various angles. To reduce the information loss during the process of merging, we develop a new model with a weighting module that dynamically determines the importance of each of the scanning angles. Using the proposed module, the loss of information is minimal, so the precision of the detection model is comparable to the model tested on each of the images separately. Using the merged images input, the analysis can be accelerated by almost 15 times.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA