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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control)
Zamani Md Sani
Universiti Teknikal Malaysia Melaka
Computer Science & IT Electrical & Electronics Engineering Engineering

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Journal : International Journal of Electrical and Computer Engineering

 1 
Real-Time Video Processing using Contour Numbers and Angles for Non-urban Road Marker Classification Zamani Md Sani; Hadhrami Abd Ghani; Rosli Besar; Azizul Azizan; Hafiza Abas
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (580.324 KB) | DOI: 10.11591/ijece.v8i4.pp2540-2548

Abstract

Road users make vital decisions to safely maneuver their vehicles based on the road markers, which need to be correctly classified. The road markers classification is significantly important especially for the autonomous car technology. The current problems of extensive processing time and relatively lower average accuracy when classifying up to five types of road markers are addressed in this paper. Two novel real time video processing methods are proposed by extracting two formulated features namely the contour number, , and angle, ???? to classify the road markers. Initially, the camera position is calibrated to obtain the best Field of View (FOV) for identifying a customized Region of Interest (ROI). An adaptive smoothing algorithm is performed on the ROI before the contours of the road markers and the corresponding two features are determined. It is observed that the achievable accuracy of the proposed methods at several non-urban road scenarios is approximately 96% and the processing time per frame is significantly reduced when the video resolution increases as compared to that of the existing approach.
Advances in lane marking detection algorithms for all-weather conditions Hadhrami Ab Ghani; Rosli Besar; Zamani Md Sani; Mohd Nazeri Kamaruddin; Syabeela Syahali; Atiqullah Mohamed Daud; Aerun Martin
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp3365-3373

Abstract

Driving vehicles in all-weather conditions is challenging as the lane markers tend to be unclear to the drivers for detecting the lanes. Moreover, the vehicles will move slower hence increasing the road traffic congestion which causes difficulties in detecting the lane markers especially for advanced driving assistance systems (ADAS). Therefore, this paper conducts a thorough review on vision-based lane marking detection algorithms developed for all-weather conditions. The review methodology consists of two major areas, which are a review on the general system models employed in the lane marking detection algorithms and a review on the types of weather conditions considered for the algorithms. Throughout the review process, it is observed that the lane marking detection algorithms in literature have mostly considered weather conditions such as fog, rain, haze and snow. A new contour-angle method has also been proposed for lane marker detection. Most of the research work focus on lane detection, but the classification of the types of lane markers remains a significant research gap that is worth to be addressed for ADAS and intelligent transport systems.
Co-Authors Aerun Martin Atiqullah Mohamed Daud Azizul Azizan Azizul Azizan Hadhrami Ab Ghani Hadhrami Abd Ghani Hadhrami Abd Ghani Hadhrami Abdul Ghani Hafiza Abas Hamzah Abdulmalek Al-Haimi Kok Jia Quan Mohd Nazeri Kamaruddin Rosli Besar Rosli Besar Samsul Ariffin Abdul Karim Syabeela Syahali Tarmizi Ahmad Izzudin Tarmizi Bin Ahmad Izzuddin