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Defect detection in C-scan maps
Pattern Recognition and Image Analysis, 2007An image processing procedure is proposed aiming at detecting porosity defects in materials used in the aerospace industry by means of the analysis of C-scan images obtained by ultrasound inspection techniques. An image is described through a number of features, which are then analyzed in order to evaluate the similarity of an unknown examined image ...
Bozzi E +4 more
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Fabrication of a novel C-scan photoacoustic imaging camera
2015 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2015Our objective is to provide researchers with an inexpensive and fast photoacoustic imaging (PAI) device for exvivo studies. We implement this using an acoustic lens based focusing idea together with photoacoustic technology, resulting in a prototype imaging system. A complete photoacoustic imaging system simulation modeling is presented.
Bhargava Chinni +7 more
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Neural network correction of ultrasonic C-scan images
Ultrasonics, 1999A neural network-based approach to the correction of C-scan images is presented. This allows the effects of a finite ultrasonic beam diameter in an immersion experiment to be considered, by training the network on a series of defects of known characteristics. The result is an image which is a better representation of the actual defect.
D A, Hutchins +3 more
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Ultrasonic C-scan imaging for material characterization
Ultrasonics, 1993Abstract Advances in the field have enabled ultrasonic C-scan imaging to go beyond its classical application of detecting large single flaws to meet the challenge of non-destructive evaluation for modern engineered structures and new materials. Increased frequency of operation and novel transducer designs have led to micrometre resolution limits for ...
G.A. Gordon, S. Canumalla, B.R. Tittmann
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Automated Ultrasonic Testing of Materials based on C-scan Flaw Classification
2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA), 2021The analysis of the data in non-destructive ultrasonic testing of materials is a very time- intensive task. To alleviate the aforementioned strain on the human expert inspectors, a plethora of assisted analysis methods based on deep learning have been developed recently.
Branimir Filipovic +5 more
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Evaluation of ultrasonic C-scan attenuation image
IEEE 1991 Ultrasonics Symposium, 2002Temporal averaging and homomorphic processing, which extract the local ultrasonic wavelet and estimate the attenuation coefficient, have been incorporated into C-scan imaging to generate and attenuation map. The variation of this map displays changes in the scattering cross section and in the absorption of materials.
T. Wang, J. Saniie
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Defect Monitoring of CFRP with Ultrasonic C-Scan Method
Advanced Materials Research, 2011In this study, carbon fiber reinforced polymer (CFRP) laminates that were under three-point bending load within and without initial impact damage, were detected and monitored by ultrasonic C-scan method. The defect morphology at various load levels was recorded.
Peng Li +5 more
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Improved C-scan imaging using a Bayesian approach
2010 IEEE International Ultrasonics Symposium, 2010Conventional ultrasonic C-scan imaging in composite materials typically employs peak amplitude extraction where the obtained image quality is extremely dependent on the gate setup on the ultrasonic acquisition hardware. Additionally structural noise created by scattering phenomenon is often high enough to bury meaningful reflection echoes, due to the ...
K. S. Ho +4 more
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