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A Neural network based technique for automatic classification of road cracks

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conference contribution
posted on 06.12.2017, 00:00 by J Bray, X Li, W He, Brijesh VermaBrijesh Verma
This paper presents a neural network based technique for the classification of segments of road images into cracks and normal images. The density and histogram features are extracted. The features are passed to a neural network for the classification of images into images with and without cracks. Once images are classified into cracks and non-cracks, they are passed to another neural network for the classification of a crack type after segmentation. Some experiments were conducted and promising results were obtained. The selected results and a comparative analysis are included in this paper.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Start Page

1886

End Page

1891

Number of Pages

6

Start Date

01/01/2006

ISBN-10

0780394895

Location

Vancouver, Canada

Publisher

IEEE

Place of Publication

Piscatway, NJ

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Canal Industrial Pty. Ltd; Faculty of Business and Informatics; University of Queensland;

Era Eligible

Yes

Name of Conference

International Joint Conference on Neural Networks;IEEE International Conference on Fuzzy Systems;Congress on Evolutionary Computation;IEEE World Congress on Computational Intelligence;IEEE International Conference on Neural Networks