Real-time vehicle classification and counting on roads using camera and image processing techniques

Azmi, Muhammad Adib (2024) Real-time vehicle classification and counting on roads using camera and image processing techniques. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Real-time vehicle classification and counting on roads using camera and image processing techniques holds immense potential for revolutionizing traffic management and transportation systems. This system offers precise and timely data on traffic patterns, facilitating well-informed decision-making and allocation of resources. Nevertheless, there are numerous obstacles that impede its efficient execution, such as precise identification and monitoring of vehicles in intricate situations, categorization under different circumstances, managing large amounts of traffic, and ensuring reliable performance in varying contexts. The objective of this research is to tackle these difficulties by creating a computer vision system that utilises image processing and machine learning to automatically categorise and quantify cars. The system will utilise characteristics such as dimensions, form, and hue to identify and monitor vehicles in real-time, ultimately classifying them into categories such as automobiles, trucks, buses, and motorcycles. The desired result is a system that can do real-time video analysis, accurately detecting vehicles approaching from either direction up to a distance of 300 metres. This system would provide live traffic monitoring with minimal latency. This study will make a substantial contribution to the improvement of real-time vehicle categorization and counting technologies by effectively addressing the highlighted issues and attaining the project objectives. The method has practical uses in enhancing traffic management, analysing congestion, and facilitating urban planning, hence resulting in transportation systems that are more efficient and dependable.

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