Abstract
Serving as a critical feature of vehicle flow in Intelligent Transportation System (ITS) of Smart City, license plate information has been applied in many momentous transportation applications. However, ITS suffers from the low accuracy of license plate recognition due to changeful and uncontrollable environment and machinery malfunction from traffic equipment deployed on a large scale. Therefore, it is challenging for license plate recognition to satisfy high accuracy and low latency in the condition of large-scale traffic data sets. In this paper, a Heuristic License Plate Correction Method, named HelpMe, is proposed to address the challenges above. It aims at recognizing and correcting the incorrect license plate information in real-time with high accuracy. Technically, a heuristic method is adopted to guide the correction process. Moreover, in order to process the large-scale data sets efficiently, HelpMe is implemented on HANA cluster (an in-memory database). Finally, extensive experiments are conducted on a real-world data set to evaluate the feasibility and efficiency of HelpMe.
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Jia, G., Tao, X., Liu, Y., Dou, W. (2015). HelpMe: A Heuristic License Plate Correction Method for Big Data Application. In: Cao, J., Wen, L., Liu, X. (eds) Process-Aware Systems. PAS 2014. Communications in Computer and Information Science, vol 495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46170-9_8
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DOI: https://doi.org/10.1007/978-3-662-46170-9_8
Publisher Name: Springer, Berlin, Heidelberg
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