30 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationAVSS2006
EditorsMassimo Piccardi
Place of PublicationUSA
Number of pages1
ISBN (Electronic)0769526888
Publication statusPublished - 2006
EventIEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) - Sydney, Australia, Australia
Duration: 22 Nov 200624 Nov 2006


ConferenceIEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)


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