Vehicle Classification System Using Viola
Jones and Multi-Layer Perceptron
Tarig Almehmadi1, Zaw Zaw Htike2
1 Department of Electrical Engineering, University of Malaya,
Malaysia
2Department
of Mechatronics, International Islamic University, Malaysia
Abstract: The automatic vehicle classification system has
emerged as an important field of study in image processing and machine vision
technologies’ implementation because of its variety of applications. Despite
many alternative solutions for the classification issue, the vision-based
approaches remain the dominant solutions due to their ability to provide a larger
number of parameters than other approaches. To date, several approaches with
various methods have been implemented to classify vehicles. The fully automatic
classification systems constitute a huge barrier for unmanned applications and
advanced technologies. This project presents software for a vision-based
vehicle classifier using multiple Viola-Jones detectors, moment invariants
features, and a multi-layer perceptron neural network to distinguish between
different classes. The results obtained in this project show the software’s
ability to detect and locate vehicles perfectly in real time via live camera
input.
Keywords: Automatic vehicle classification, viola-jones detection, moment
invariants, neural network.