The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 31-568
Full Name: Cristian Molder
Position: Lecturer
Age: ON
Sex: Male
Address: 81-83 George Cosbuc blvd., Bucharest
Country: ROMANIA
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E-mail address: cristianmolder@gmail.com
Other E-mails: cristianmolder@yahoo.fr
Title of the Paper: Decision Fusion for Improved Automatic License Plate Recognition
Authors as they appear in the Paper: Cristian Molder, Mircea Boscoianu, Mihai I. Stanciu, Iulian C. Vizitiu
Email addresses of all the authors: cristianmolder@gmail.com, mircea_boscoianu@yahoo.co.uk, stanciu_mihai_ionut@yahoo.com, iulian_vizitiu@yahoo.com
Number of paper pages: 10
Abstract: Automatic license plate recognition (ALPR) is a pattern recognition application of great importance for access, traffic surveillance and law enforcement. Therefore many studies are concentrated on creating new algorithms or improving their performance. Many authors have presented algorithms that are based on individual methods such as skeleton features, neural networks or template matching for recognizing the license plate symbols. In this paper we present a novel approach for decisional fusion of several recognition methods, as well as new classification features. The classification results are proven to be significantly better that those obtained for each method considered individually. For better results, syntax corrections are also considered. Several trainable and non-trainable decisional fusion rules have been taken into account, evidencing each of the classification methods at their best. Experimental results are shown, the results being very encouraging by !
obtaining a symbol good recognition rate (GRC) of more than 99.4\% on a real license plate database.
Keywords: Licence plate, ALPR, Pattern recognition, Skeleton features, Neural
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