PAVEMENT DISTRESS EVALUATION USING FUZZY LOGIC AND MOMENT INVARIANTS
A novel approach of applying the theory of fuzzy sets and moment invariants to analyze pavement images in proposed in this paper. By applying the theory of fuzzy sets and calculating moment invariants from different types of distress, features are obtained. Then, a back-propagation neural network is used to classify these features. The crack density is used to obtain extent information. This approach is illustrated using randomly selected samples from NCHRP Project 1-27 video images of real cracks. Based on these samples, the feasibility of using the theory of fuzzy sets and moment invariants to classify different types of crack is proven. High accuracy of classification is also obtained.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/0309061660
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Supplemental Notes:
- This paper appears in Transportation Research Record No. 1505, Pavement Monitoring and Evaluation Issues. Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved
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Authors:
- Chou, JaChing
- O'Neill, Wende A
- Cheng, Hengda
- Publication Date: 1995
Language
- English
Media Info
- Features: Figures; References; Tables;
- Pagination: p. 39-46
- Monograph Title: Pavement monitoring and evaluation issues
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Serial:
- Transportation Research Record
- Issue Number: 1505
- Publisher: Transportation Research Board
- ISSN: 0361-1981
Subject/Index Terms
- TRT Terms: Accuracy; Classification; Defects; Fuzzy sets; Image analysis; Image processing; Neural networks; Pavement distress; Pavements
- Old TRIS Terms: Moment invariants
- Subject Areas: Highways; Pavements; I23: Properties of Road Surfaces;
Filing Info
- Accession Number: 00715554
- Record Type: Publication
- ISBN: 0309061660
- Files: TRIS, TRB
- Created Date: Jan 4 1996 12:00AM