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Integrating the Symmetry Image and Improved Sparse Representation for Railway Fastener Classification and Defect Recognition
Joint Authors
Liu, Jiajia
Li, Bailin
Xiong, Ying
He, Biao
Li, Li
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-11-09
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The detection of fastener defects is an important task for ensuring the safety of railway traffic.
The earlier automatic inspection systems based on computer vision can detect effectively the completely missing fasteners, but they have weaker ability to recognize the partially worn ones.
In this paper, we propose a method for detecting both partly worn and completely missing fasteners, the proposed algorithm exploits the first and second symmetry sample of original testing fastener image and integrates them for improved representation-based fastener recognition.
This scheme is simple and computationally efficient.
The underlying rationales of the scheme are as follows: First, the new virtual symmetrical images really reflect some possible appearance of the fastener; then the integration of two judgments of the symmetrical sample for fastener recognition can somewhat overcome the misclassification problem.
Second, the improved sparse representation method discarding the training samples that are “far” from the test sample and uses a small number of samples that are “near” to the test sample to represent the test sample, so as to perform classification and it is able to reduce the side-effect of the error identification problem of the original fastener image.
The experimental results show that the proposed method outperforms state-of-the-art fastener recognition methods.
American Psychological Association (APA)
Liu, Jiajia& Li, Bailin& Xiong, Ying& He, Biao& Li, Li. 2015. Integrating the Symmetry Image and Improved Sparse Representation for Railway Fastener Classification and Defect Recognition. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073887
Modern Language Association (MLA)
Liu, Jiajia…[et al.]. Integrating the Symmetry Image and Improved Sparse Representation for Railway Fastener Classification and Defect Recognition. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1073887
American Medical Association (AMA)
Liu, Jiajia& Li, Bailin& Xiong, Ying& He, Biao& Li, Li. Integrating the Symmetry Image and Improved Sparse Representation for Railway Fastener Classification and Defect Recognition. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073887
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073887