An intelligent strategy for checking the annual inspection status of motorcycles based on license plate recognition

Authors:
Yo-Ping Huang;Chien-Hung Chen;Yueh-Tsun Chang;Frode Eika Sandnes
Affiliations:
Department of Electrical Engineering, National Taipei University of Technology, Taipei 10608, Taiwan;Department of Computer Science and Engineering, Tatung University, Taipei 10451, Taiwan;Department of Computer Science and Engineering, Tatung University, Taipei 10451, Taiwan;Faculty of Engineering, Oslo University College, Oslo, Norway
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

License plate recognition techniques have been successfully applied to the management of stolen cars, management of parking lots and traffic flow control. This study proposes a license plate based strategy for checking the annual inspection status of motorcycles from images taken along the roadside and at designated inspection stations. Both a UMPC (Ultra Mobile Personal Computer) with a web camera and a desktop PC are used as hardware platforms. The license plate locations in images are identified by means of integrated horizontal and vertical projections that are scanned using a search window. Moreover, a character recovery method is exploited to enhance the success rate. Character recognition is achieved using both a back propagation artificial neural network and feature matching. The identified license plate can then be compared with entries in a database to check the inspection status of the motorcycle. Experiments yield a recognition rate of 95.7% and 93.9% based on roadside and inspection station test images, respectively. It takes less than 1s on a UMPC (Celeron 900MHz with 256MB memory) and about 293ms on a PC (Intel Pentium 4 3.0GHz with 1GB memory) to correctly recognize a license plate. Challenges associated with recognizing license plates from roadside and designated inspection stations images are also discussed.