Design and development of image based lane warning and anti-collision detection system / M.W. Ahmed ... [et al.]
The increasing rate of car accidents worldwide triggered the necessity to develop a system that can help in reducing that figure. In this paper, an image processing based Lane Departure Warning System (LDWS) and Forward Collision Warning (FCW) were introduced in one system namely smart Inner Rear Vi...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM),
2018.
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| Subjects: | |
| Online Access: | Get fulltext View Fulltext in UiTM IR |
| LEADER | 01987 am a22002533u 4500 | ||
|---|---|---|---|
| 001 | 41022 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Ahmed, M.W. |e author |
| 700 | 1 | 0 | |a Abidin, Z.Z. |e author |
| 700 | 1 | 0 | |a Mustafah, Y.M. |e author |
| 700 | 1 | 0 | |a Mourshid, S.K. |e author |
| 700 | 1 | 0 | |a Abdelhalim, M.A. |e author |
| 700 | 1 | 0 | |a Rahman, H.A |e author |
| 700 | 1 | 0 | |a Sulaiman, S.N. |e author |
| 245 | 0 | 0 | |a Design and development of image based lane warning and anti-collision detection system / M.W. Ahmed ... [et al.] |
| 260 | |b Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM), |c 2018. | ||
| 856 | |z Get fulltext |u https://ir.uitm.edu.my/id/eprint/41022/1/41022.pdf | ||
| 856 | |z View Fulltext in UiTM IR |u https://ir.uitm.edu.my/id/eprint/41022/ | ||
| 520 | |a The increasing rate of car accidents worldwide triggered the necessity to develop a system that can help in reducing that figure. In this paper, an image processing based Lane Departure Warning System (LDWS) and Forward Collision Warning (FCW) were introduced in one system namely smart Inner Rear View Mirror (IRVM). This system will monitor the road parameters and give a warning to the driver to be attentive whenever there is deviation from the lane or possible collision. The novelty of this project relies in reducing the cost of such a system to be affordable to everyone as those systems are currently expensive and exist only in luxury cars. This system utilize OpenCV Inverse Perspective Mapping (IPM), Probabilistic Hough Transform (PHT) and Haar classifier. Raspberry Pi single board computer is used as a platform to process the real-time videos. A preliminary result shows that the system is capable of lane markings detection in different roads condition and traffic situation and able to detect cars in front of the driver with more than 93% accuracy. | ||
| 546 | |a en | ||
| 650 | 0 | 4 | |a TJ Mechanical engineering and machinery |
| 650 | 0 | 4 | |a Machine design and drawing |
| 650 | 0 | 4 | |a Machine construction (General) |
| 655 | 7 | |a Article | |