Development of a license plate recognition system for a non-ideal environment

Lorita Angeline and Hui, Keng Lau and Bablu Kumar Ghosh and Hui, Hwang Goh and Tze, Kenneth Kin Teo (2012) Development of a license plate recognition system for a non-ideal environment. International Journal of Simulation Systems, Science & Technology, IJSSST, 13 (3C). pp. 26-33. ISSN 1473-804x

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A new algorithm for license plate character recognition system is proposed on the basis of Signature analysis properties and features extraction. Signature analysis has been used to locate license plate region and its properties can be further utilised in supporting and affirming the license plate character recognition. This paper presents the implementation of Signature Analysis combined with Features Extraction to form feature vector for each character with a length of 56. Implementation of these two methods is used in tracking of vehicle’s automatic license plate recognition system (ALPR). The developed ALPR comprises of three phase. The recognition stage utilised the vector to be trained in a simple multi-layer feed-forward back-propagation Neural Network with 56 inputs and 34 neurons in its output layer. The network is trained with both ideal and noisy characters. The results obtained show that the proposed system is capable to recognise both ideal and non-ideal license plate characters. The system also capable to tackle the common character misclassification problems due to similarity in characters.

Item Type: Article
Keyword: ALPR, Signature Analysis, Features Extraction, Character Recognition, License Plate, Artificial Neural Network
Subjects: T Technology > TJ Mechanical engineering and machinery
Department: FACULTY > Faculty of Engineering
Date Deposited: 22 Mar 2018 11:39
Last Modified: 22 Mar 2018 11:39

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