Feature extraction for underground object reconstruction from Ground Penetrating Radar (GPR) data
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Universiti Malaysia Perlis (UniMAP)
2022
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| Online Access: | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/76847 |
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my.unimap-768472022-11-10T00:57:03Z Feature extraction for underground object reconstruction from Ground Penetrating Radar (GPR) data S. A., Abdul Shukor S. A., Abdul Shukor Havenderpal, Singh Nurush Syamimie, Mahmud H., Ali A. F., Ahmad Zaidi M. S., Zanar Azalan T. S., Tengku Amran M. R., Ahmad shazmin@unimap.edu.my Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis (UniMAP) Malaysian Nuclear Agency Drop-flow algorithm GPR Underground object detection and reconstruction Link to publisher's homepage at http://jere.unimap.edu.my Ground Penetrating Radar (GPR) is very beneficial for underground object scanning and detection. It utilises radar pulses as the signal, hence it able to penetrate surfaces in obtaining the underneath information without disturbing and destructing the ground. However, its radargram output in hyperbolic signal are very challenging to be analysed. Thus, suitable algorithm has to be designed and developed to interpret the data. This work highlights on the usage of drop-flow algorithm in detecting important features of the hyperbolic signal. Previous study has shown that these features is promising in understanding and further, reconstructing the GPR data. Results show that the features extracted from the hyperbolic signal able to be identified for further processing, which is necessary for visualization purpose. 2022-11-10T00:57:03Z 2022-11-10T00:57:03Z 2022 Article Journal of Engineering Research and Education, vol.14, 2022, pages 25-33 1823-2981 (print) 2232-1098 (online) http://dspace.unimap.edu.my:80/xmlui/handle/123456789/76847 en Universiti Malaysia Perlis (UniMAP) |
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Asia |
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Malaysia |
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Universiti Malaysia Perlis |
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| language |
English |
| topic |
Drop-flow algorithm GPR Underground object detection and reconstruction |
| spellingShingle |
Drop-flow algorithm GPR Underground object detection and reconstruction S. A., Abdul Shukor S. A., Abdul Shukor Havenderpal, Singh Nurush Syamimie, Mahmud H., Ali A. F., Ahmad Zaidi M. S., Zanar Azalan T. S., Tengku Amran M. R., Ahmad Feature extraction for underground object reconstruction from Ground Penetrating Radar (GPR) data |
| description |
Link to publisher's homepage at http://jere.unimap.edu.my |
| author2 |
shazmin@unimap.edu.my |
| author_facet |
shazmin@unimap.edu.my S. A., Abdul Shukor S. A., Abdul Shukor Havenderpal, Singh Nurush Syamimie, Mahmud H., Ali A. F., Ahmad Zaidi M. S., Zanar Azalan T. S., Tengku Amran M. R., Ahmad |
| format |
Article |
| author |
S. A., Abdul Shukor S. A., Abdul Shukor Havenderpal, Singh Nurush Syamimie, Mahmud H., Ali A. F., Ahmad Zaidi M. S., Zanar Azalan T. S., Tengku Amran M. R., Ahmad |
| author_sort |
S. A., Abdul Shukor |
| title |
Feature extraction for underground object reconstruction from Ground Penetrating Radar (GPR) data |
| title_short |
Feature extraction for underground object reconstruction from Ground Penetrating Radar (GPR) data |
| title_full |
Feature extraction for underground object reconstruction from Ground Penetrating Radar (GPR) data |
| title_fullStr |
Feature extraction for underground object reconstruction from Ground Penetrating Radar (GPR) data |
| title_full_unstemmed |
Feature extraction for underground object reconstruction from Ground Penetrating Radar (GPR) data |
| title_sort |
feature extraction for underground object reconstruction from ground penetrating radar (gpr) data |
| publisher |
Universiti Malaysia Perlis (UniMAP) |
| publishDate |
2022 |
| url |
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/76847 |
| _version_ |
1751537977033490432 |
| score |
13.214268 |