An intelligent strategy for checking the annual inspection status of motorcycles based on license plate recognition
2008; Elsevier BV; Volume: 36; Issue: 5 Linguagem: Inglês
10.1016/j.eswa.2008.12.006
ISSN1873-6793
AutoresYo‐Ping Huang, Chien‐Hung Chen, Yueh-Tsun Chang, Frode Eika Sandnes,
Tópico(s)Advanced Neural Network Applications
ResumoLicense 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 1 s on a UMPC (Celeron 900 MHz with 256 MB memory) and about 293 ms on a PC (Intel Pentium 4 3.0 GHz with 1 GB memory) to correctly recognize a license plate. Challenges associated with recognizing license plates from roadside and designated inspection stations images are also discussed.
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