DocumentCode :
1068334
Title :
Automated flaw detection in aluminum castings based on the tracking of potential defects in a radioscopic image sequence
Author :
Mery, Domingo ; Filbert, Dieter
Author_Institution :
Dept. de Ingenieria Informatica, Univ. de Santiago de Chile, Chile
Volume :
18
Issue :
6
fYear :
2002
fDate :
12/1/2002 12:00:00 AM
Firstpage :
890
Lastpage :
901
Abstract :
Presents a method for inspecting aluminum castings automatically from a sequence of radioscopic images taken at different positions of the casting. The classic image-processing methods for flaw detection of aluminum castings use a bank of filters to generate an error-free reference image. This reference image is compared with the real radioscopic image, and flaws are detected at the pixels where the difference between them is considerable. However, the configuration of each filter depends strongly on the size and shape of the structure of the casting under inspection. A two-step technique is proposed to detect flaws automatically and that uses a single filter. First, the method identifies potential defects in each image of the sequence, and second, it matches and tracks them from image to image. The key idea of the paper is to consider as false alarms those potential defects which cannot be tracked in the sequence. The robustness and reliability of the method have been verified on both real data in which synthetic flaws have been added and real radioscopic image sequences recorded from cast aluminum wheels with known defects. Using this method, the real defects can be detected with high certainty. This approach achieves good discrimination from false alarms.
Keywords :
X-ray imaging; computer vision; flaw detection; image segmentation; image sequences; X-ray testing; aluminum castings; automated flaw detection; automated inspection; computer vision; false alarms; image segmentation; potential defects tracking; radioscopic image sequence; reliability; robustness; two-step technique; Aluminum; Casting; Filters; Image sequences; Inspection; Nondestructive testing; Wheels; X-ray detection; X-ray detectors; X-ray imaging;
fLanguage :
English
Journal_Title :
Robotics and Automation, IEEE Transactions on
Publisher :
ieee
ISSN :
1042-296X
Type :
jour
DOI :
10.1109/TRA.2002.805646
Filename :
1159007
Link To Document :
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