Asphalt Mixture Segregation Detection: Digital Image Processing Approach
| Autor: | Amirmasoud Hamedi, Mohamadtaqi Baqersad, Hesham Ali, Mojtaba Mohammadafzali |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Materials science
Article Subject business.industry 0211 other engineering and technologies General Engineering 020101 civil engineering Pattern recognition Image processing 02 engineering and technology Linear discriminant analysis Grayscale Standard deviation 0201 civil engineering Visual inspection Asphalt Histogram 021105 building & construction Digital image processing lcsh:TA401-492 General Materials Science lcsh:Materials of engineering and construction. Mechanics of materials Artificial intelligence business Simulation |
| Zdroj: | Advances in Materials Science and Engineering, Vol 2017 (2017) |
| ISSN: | 1687-8434 |
| DOI: | 10.1155/2017/9493408 |
| Popis: | Segregation determination in the asphalt pavement is an issue causing many disputes between agencies and contractors. The visual inspection method has commonly been used to determine pavement texture and in-place core density test used for verification. Furthermore, laser-based devices, such as the Florida Texture Meter (FTM) and the Circular Track Meter (CTM), have recently been developed to evaluate the asphalt mixture texture. In this study, an innovative digital image processing approach is used to determine pavement segregation. In this procedure, the standard deviation of the grayscale image frequency histogram is used to determine segregated regions. Linear Discriminate Analysis (LDA) is then implemented on the obtained standard deviations from image processing to classify pavements into the segregated and nonsegregated areas. The visual inspection method is utilized to verify this method. The results have demonstrated that this new method is a robust tool to determine segregated areas in newly paved FC9.5 pavement types. |
| Databáze: | OpenAIRE |
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