Asphalt Mixture Segregation Detection: Digital Image Processing Approach
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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2017/9493408 |
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| _version_ | 1832553623975886848 |
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| author | Mohamadtaqi Baqersad Amirmasoud Hamedi Mojtaba Mohammadafzali Hesham Ali |
| author_facet | Mohamadtaqi Baqersad Amirmasoud Hamedi Mojtaba Mohammadafzali Hesham Ali |
| author_sort | Mohamadtaqi Baqersad |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-a1325c1643644f75a761f325ca059b8d |
| institution | Kabale University |
| issn | 1687-8434 1687-8442 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Materials Science and Engineering |
| spelling | doaj-art-a1325c1643644f75a761f325ca059b8d2025-02-03T05:53:36ZengWileyAdvances in Materials Science and Engineering1687-84341687-84422017-01-01201710.1155/2017/94934089493408Asphalt Mixture Segregation Detection: Digital Image Processing ApproachMohamadtaqi Baqersad0Amirmasoud Hamedi1Mojtaba Mohammadafzali2Hesham Ali3Department of Civil and Environmental Engineering, Florida International University, 10555 West Flagler Street, Miami, FL 33174, USADepartment of Civil and Environmental Engineering, Florida International University, 10555 West Flagler Street, Miami, FL 33174, USADepartment of Civil and Environmental Engineering, Florida International University, 10555 West Flagler Street, Miami, FL 33174, USADepartment of Civil and Environmental Engineering, Florida International University, 10555 West Flagler Street, Miami, FL 33174, USASegregation 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.http://dx.doi.org/10.1155/2017/9493408 |
| spellingShingle | Mohamadtaqi Baqersad Amirmasoud Hamedi Mojtaba Mohammadafzali Hesham Ali Asphalt Mixture Segregation Detection: Digital Image Processing Approach Advances in Materials Science and Engineering |
| title | Asphalt Mixture Segregation Detection: Digital Image Processing Approach |
| title_full | Asphalt Mixture Segregation Detection: Digital Image Processing Approach |
| title_fullStr | Asphalt Mixture Segregation Detection: Digital Image Processing Approach |
| title_full_unstemmed | Asphalt Mixture Segregation Detection: Digital Image Processing Approach |
| title_short | Asphalt Mixture Segregation Detection: Digital Image Processing Approach |
| title_sort | asphalt mixture segregation detection digital image processing approach |
| url | http://dx.doi.org/10.1155/2017/9493408 |
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