A machine learning approach for detecting and tracking road boundary lanes
Road boundary lanes are one of the serious causes of road accidents and it affects the driver and people’s safety. Detecting road boundary lanes is a challenging task for both computer vision and machine learning approaches. In recent years many machine learning algorithms have been deploying but th...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-03-01
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| Series: | ICT Express |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S240595952030240X |
| _version_ | 1818622810864484352 |
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| author | Satish Kumar Satti K. Suganya Devi Prasenjit Dhar P. Srinivasan |
| author_facet | Satish Kumar Satti K. Suganya Devi Prasenjit Dhar P. Srinivasan |
| author_sort | Satish Kumar Satti |
| collection | DOAJ |
| description | Road boundary lanes are one of the serious causes of road accidents and it affects the driver and people’s safety. Detecting road boundary lanes is a challenging task for both computer vision and machine learning approaches. In recent years many machine learning algorithms have been deploying but they failed to produce high efficiency and accuracy. This paper presents a novel approach to alert the driver when the car leaps beyond the Road boundary lanes by employing machine learning techniques to avoid road mishaps and ensuring driving safety. Performance is assessed through the generation of experimental results on the dataset. When compared with state-of-the-art lane detection techniques, the proposed technique produced high precision and high efficiency. |
| first_indexed | 2024-12-16T18:31:05Z |
| format | Article |
| id | doaj.art-7426a9d417c849c993e8a3e1be2ff6f7 |
| institution | Directory Open Access Journal |
| issn | 2405-9595 |
| language | English |
| last_indexed | 2024-12-16T18:31:05Z |
| publishDate | 2021-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | ICT Express |
| spelling | doaj.art-7426a9d417c849c993e8a3e1be2ff6f72022-12-21T22:21:17ZengElsevierICT Express2405-95952021-03-017199103A machine learning approach for detecting and tracking road boundary lanesSatish Kumar Satti0K. Suganya Devi1Prasenjit Dhar2P. Srinivasan3Computer Science and Engineering, National Institute of Technology Silchar, IndiaComputer Science and Engineering, National Institute of Technology Silchar, India; Corresponding author.Computer Science and Engineering, National Institute of Technology Silchar, IndiaPhysics, National Institute of Technology, Silchar, IndiaRoad boundary lanes are one of the serious causes of road accidents and it affects the driver and people’s safety. Detecting road boundary lanes is a challenging task for both computer vision and machine learning approaches. In recent years many machine learning algorithms have been deploying but they failed to produce high efficiency and accuracy. This paper presents a novel approach to alert the driver when the car leaps beyond the Road boundary lanes by employing machine learning techniques to avoid road mishaps and ensuring driving safety. Performance is assessed through the generation of experimental results on the dataset. When compared with state-of-the-art lane detection techniques, the proposed technique produced high precision and high efficiency.http://www.sciencedirect.com/science/article/pii/S240595952030240XReal time transportationRoad boundary lane detectionConvolutional neural networksMachine learning |
| spellingShingle | Satish Kumar Satti K. Suganya Devi Prasenjit Dhar P. Srinivasan A machine learning approach for detecting and tracking road boundary lanes ICT Express Real time transportation Road boundary lane detection Convolutional neural networks Machine learning |
| title | A machine learning approach for detecting and tracking road boundary lanes |
| title_full | A machine learning approach for detecting and tracking road boundary lanes |
| title_fullStr | A machine learning approach for detecting and tracking road boundary lanes |
| title_full_unstemmed | A machine learning approach for detecting and tracking road boundary lanes |
| title_short | A machine learning approach for detecting and tracking road boundary lanes |
| title_sort | machine learning approach for detecting and tracking road boundary lanes |
| topic | Real time transportation Road boundary lane detection Convolutional neural networks Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S240595952030240X |
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