چکیده (انگلیسی):

On road vehicles have increased in numbers and
monitoring them is a challenging task. In common areas of public
crowd people and vehicles are common objects for monitoring. The
proposed system aims at detecting number plate information
indicating the possibility for security relevant issues. Existing
system performs recognition mainly by using license plate alone.
Addition of the features (logo, colour, shape) will increase the
security of the system. Identification of the number plate region has
been done by Blob detection method at the predefined aspect ratio.
After detection, extraction of the number plate information using
Eigen value regularization method. Further, two methodology
included in this study are, identifying the tampered region in a car
image either by extracting HoG feature in the spatial domain or
block differences in DCT coefficients and their corresponding
histogram in the transform domain respectively. Experimental results
for the given car dataset describes the identification of the number
plate region and tampered region quantitatively. The work presents
detailed results of how the proposed approach gives better results
using HoG approach. The approach gives good results in videos of
cars recorded in frontal view in good lighting conditions. The paper
in overall suggest a hybrid approach for detecting number plate
information in cars taken in good lighting conditions.