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Aymen Fadhil Abbas
Universiti Teknologi Malaysia
Electrical & Electronics Engineering

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Recognition of vehicle make and model in low light conditions Aymen Fadhil Abbas; Usman Ullah Sheikh; Mohd Norzali Haji Mohd
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (476.518 KB) | DOI: 10.11591/eei.v9i2.1865

Abstract

This paper presents a method for vehicle make and model recognition (MMR) in low lighting conditions. While many MMR methods exist in the literature, these methods are designed to be used only in perfect operating conditions. The various camera configuration, lighting condition, and viewpoints cause variations in image quality.  In the presented method, the vehicle is first detected, image enhancement is then carried out on the detected front view of the vehicle, followed by features extraction and classification. The performance is then examined on a low-light dataset. The results show around 6% improvement in the ability of MMR with the use of image enhancement over the same recognition model without image enhancement.
Co-Authors Mohd Norzali Haji Mohd Usman Ullah Sheikh