A study of two image-recognition algorithms for the classification of flaws in a test object according to its digital image

The mathematical model of a digital radiation image is given that corresponds to a test object that contains two types of defects, namely, pores and cracks (or non-penetrating defects). Two algorithms for automatic image recognition of these defects on a digital radiation image of an object are give...

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Bibliographic Details
Published in:	Russian journal of nondestructive testing Vol. 51; no. 10; pp. 644 - 651
Main Authors:	Vorobeichikov, S. E., Fokin, V. A., Udod, V. A., Temnik, A. K.
Format:	Journal Article
Language:	English
Published:	Moscow Pleiades Publishing 01-10-2015
Subjects:	Algorithms Characterization and Evaluation of Materials Chemistry and Materials Science Classification Defects Digital imaging Materials Science Mathematical models Nondestructive testing Object recognition Structural Materials X-Ray Methods digital radiation image recognition algorithms test object defects
Online Access:	Get full text
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Summary:	The mathematical model of a digital radiation image is given that corresponds to a test object that contains two types of defects, namely, pores and cracks (or non-penetrating defects). Two algorithms for automatic image recognition of these defects on a digital radiation image of an object are given. The effectiveness of the algorithms was evaluated via mathematical simulation.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1061-8309 1608-3385
DOI:	10.1134/S1061830915100101