Abstract:
The utilization of vehicles increases with the increased number of populations. Unplanned
parking strategies cause additional traffic problems, waste of time, unwanted conflicts
among drivers, damages, etc. Vehicles need appropriate parking areas based on their size
and dimension to fit well. In Sri Lanka, manual processing is adopted to handle most
of the parking areas, which wastes energy, and time and causes stress. In city areas, parking
vehicles on the roadside is strictly restricted. In this paper, an automated system of
vehicle classification for allocating parking slots in public premises is proposed. This
system can capture a set of vehicle images, identify the type of vehicle, estimate the size
of the vehicle and allocate a good fit parking slot based on their dimensional and type
parameters. Geometrical or dimensional attributes and Histogram of Oriented Gradient
features are extracted, and a Support Vector Machine is used for classification. Feature
fusion is exploited to investigate the impact of fusion strategy on system performance.
Principal Component Analysis is applied to reduce the dimension of the feature vector,
which results in further significant improvement in the system performance.
