Pre-processing methods for vehicle lane detection / Muhammad Naim Mazani... [et al.]
This study presents pre-processing methods for detecting lane detection using camera and Light Detection and Ranging (LiDAR) sensor technologies. Standard image processing methods are not suitable for complicated roads with various sign on the ground. Thus, determining the right techniques for pre-p...
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| Format: | Book |
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Universiti Teknologi MARA Cawangan Pulau Pinang,
2020-06.
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| Online Access: | Link Metadata |
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| LEADER | 00000 am a22000003u 4500 | ||
|---|---|---|---|
| 001 | repouitm_33247 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Mazani, Muhammad Naim |e author |
| 700 | 1 | 0 | |a Abdul-Rahman, Shuzlina |e author |
| 700 | 1 | 0 | |a Mutalib, Sofianita |e author |
| 245 | 0 | 0 | |a Pre-processing methods for vehicle lane detection / Muhammad Naim Mazani... [et al.] |
| 260 | |b Universiti Teknologi MARA Cawangan Pulau Pinang, |c 2020-06. | ||
| 500 | |a https://ir.uitm.edu.my/id/eprint/33247/1/33247.pdf | ||
| 520 | |a This study presents pre-processing methods for detecting lane detection using camera and Light Detection and Ranging (LiDAR) sensor technologies. Standard image processing methods are not suitable for complicated roads with various sign on the ground. Thus, determining the right techniques for pre-processing such data would be a challenge. The objectives of this study are to pre-process the scanned images and apply the image recognition algorithm for lane detection. The study employed Canny Edge Detection and Hough Transform algorithms on several sets of images. A different region of interest was experimented to find the optimal one. The experimental results showed that the proposed algorithms could be practical in terms of effectively detecting road lines and generate lane detection | ||
| 546 | |a en | ||
| 690 | |a Analysis | ||
| 690 | |a Mappings (Mathematics) | ||
| 690 | |a Evolutionary programming (Computer science). Genetic algorithms | ||
| 690 | |a Malaysia | ||
| 655 | 7 | |a Article |2 local | |
| 655 | 7 | |a PeerReviewed |2 local | |
| 787 | 0 | |n https://ir.uitm.edu.my/id/eprint/33247/ | |
| 787 | 0 | |n https://uppp.uitm.edu.my | |
| 856 | 4 | 1 | |u https://ir.uitm.edu.my/id/eprint/33247/ |z Link Metadata |