Content-based image retrieval approaches to interpret ground penetrating radar data
| Autor: | Imad L. Al-Qadi, Pengcheng Shangguan |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Discrete wavelet transform
Ballast Data processing Engineering Similarity (geometry) business.industry Feature extraction Building and Construction Content-based image retrieval Ground-penetrating radar General Materials Science Computer vision Artificial intelligence business Image retrieval Civil and Structural Engineering |
| Zdroj: | Construction and Building Materials. 69:10-17 |
| ISSN: | 0950-0618 |
| DOI: | 10.1016/j.conbuildmat.2014.06.060 |
| Popis: | This paper presents a new data processing algorithm to interpret ground penetrating radar (GPR) data for quantification of railroad ballast fouling conditions. The algorithm is based on the observation that different fouling levels generate different textures in the GPR images. The algorithm was designed following the content-based image retrieval procedure, which includes two steps: feature extraction and similarity measurement. First, texture feature was extracted using discrete wavelet transform. Second, similarity measurement was performed. Laboratory GPR data were used to evaluate the accuracy of the algorithm. The accuracy was 93%, which demonstrated the effectiveness of the algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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