Image simulation for automatic license plate recognition

Raja Bala; Yonghui Zhao; Aaron Burry; Vladimir Kozitsky; Claude Fillion; Craig Saunders; José Rodríguez-Serrano

doi:10.1117/12.912453

15 February 2012 Image simulation for automatic license plate recognition

Raja Bala, Yonghui Zhao, Aaron Burry, Vladimir Kozitsky, Claude Fillion, Craig Saunders, José Rodríguez-Serrano

Proceedings Volume 8305, Visual Information Processing and Communication III; 83050Z (2012) https://doi.org/10.1117/12.912453
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

Abstract

Automatic license plate recognition (ALPR) is an important capability for traffic surveillance applications, including toll monitoring and detection of different types of traffic violations. ALPR is a multi-stage process comprising plate localization, character segmentation, optical character recognition (OCR), and identification of originating jurisdiction (i.e. state or province). Training of an ALPR system for a new jurisdiction typically involves gathering vast amounts of license plate images and associated ground truth data, followed by iterative tuning and optimization of the ALPR algorithms. The substantial time and effort required to train and optimize the ALPR system can result in excessive operational cost and overhead. In this paper we propose a framework to create an artificial set of license plate images for accelerated training and optimization of ALPR algorithms. The framework comprises two steps: the synthesis of license plate images according to the design and layout for a jurisdiction of interest; and the modeling of imaging transformations and distortions typically encountered in the image capture process. Distortion parameters are estimated by measurements of real plate images. The simulation methodology is successfully demonstrated for training of OCR.

Citation Download Citation

Raja Bala, Yonghui Zhao, Aaron Burry, Vladimir Kozitsky, Claude Fillion, Craig Saunders, and José Rodríguez-Serrano "Image simulation for automatic license plate recognition", Proc. SPIE 8305, Visual Information Processing and Communication III, 83050Z (15 February 2012); https://doi.org/10.1117/12.912453

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