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Proceedings Paper

Gradient-based Hough transform for the detection and characterization of defects during nondestructive inspection
Author(s): Lew F.C. Lew Yan Voon; Patrice Bolland; Olivier Laligant; Patrick Gorria; B. Gremillet; L. Pillet
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Paper Abstract

Ultrasonic non-destructive inspection is today a routine method in industries for the detection, localization and sizing of surface and buried defects in engineering structures. However, the analysis of the huge amount of data obtained during an ultrasonic non-destructive inspection is not a simple task and usually time consuming. This is why the data are displayed in the form of images in order to take advantage of the power of visual representation of information and image processing tools used so as to speed up the analysis problem. In ultrasonic non-destructive inspection the data are displayed in the form of mainly three types of images known as B-SCAN, C-SCAN and D-SCAN displays. The work that we shall present herein is concerned with the application of an image processing algorithm on B- SCAN displays in order to detect crack defects in thick engineering structures. This algorithm is based on the Hough transform in which a gradient analysis is performed during the computation of the Hough space. In order to decide whether a defect is present in the structure or not we need to set a threshold and analyze the Hough space. Any maximum in the Hough space which is greater than the threshold represents a defect in the structure. Due to the diversity of B-SCAN displays which may or may not contain defects, the threshold is not a fixed one and depends on the Hough space obtained.

Paper Details

Date Published: 15 April 1997
PDF: 7 pages
Proc. SPIE 3029, Machine Vision Applications in Industrial Inspection V, (15 April 1997); doi: 10.1117/12.271236
Show Author Affiliations
Lew F.C. Lew Yan Voon, Univ. de Bourgogne (France)
Patrice Bolland, Univ. de Bourgogne (France)
Olivier Laligant, Univ. de Bourgogne (France)
Patrick Gorria, Univ. de Bourgogne (France)
B. Gremillet, FRAMATOME (France)
L. Pillet, FRAMATOME (France)


Published in SPIE Proceedings Vol. 3029:
Machine Vision Applications in Industrial Inspection V
A. Ravishankar Rao; Ning S. Chang, Editor(s)

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