Abstract
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
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Mazani, Muhammad Naim UNSPECIFIED Abdul-Rahman, Shuzlina UNSPECIFIED Mutalib, Sofianita UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Analysis Q Science > QA Mathematics > Analysis > Mappings (Mathematics) Q Science > QA Mathematics > Evolutionary programming (Computer science). Genetic algorithms Q Science > QA Mathematics > Evolutionary programming (Computer science). Genetic algorithms > Malaysia |
Divisions: | Universiti Teknologi MARA, Pulau Pinang > Permatang Pauh Campus |
Journal or Publication Title: | ESTEEM Academic Journal |
UiTM Journal Collections: | UiTM Journal > ESTEEM Academic Journal (EAJ) |
ISSN: | 2289-4934 |
Volume: | 16 |
Page Range: | pp. 74-85 |
Keywords: | Image Pre-Processing, Lane Detection, Mapping, Region Of Interest |
Date: | June 2020 |
URI: | https://ir.uitm.edu.my/id/eprint/33247 |