Abstract:
Automatic number plate recognition method is
required due to increasing traffic management. In this
paper, we first briefly review some knowledge of Support
Vector Machines (SVMs). Then a number plate
recognition algorithm is proposed. This algorithm
employs an SVM to recognize numbers. The algorithm
starts from a collection of samples of numbers from
number plates. Each character is recognized by an
SVM, which is trained by some known samples in
advance. In order to recognize a number plate
correctly, all numbers are tested one by one using the
trained model. The recognition results are achieved by
finding the maximum value between the outputs of
SVMs. In this paper, experimental results based on
SVMs are given. From the experimental results, we can
make the conclusion that SVM is better than others
such as inductive learning-based number recognition.
