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26 March 2015 End-to-end system of license plate localization and recognition
Siyu Zhu, Sohail A. Dianat, Lalit K. Mestha
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Abstract
An end-to-end license plate recognition system is proposed. It is composed of preprocessing, detection, segmentation, and character recognition to find and recognize plates from camera-based still images. The system utilizes connected component (CC) properties to quickly extract the license plate region. A two-stage CC filtering is utilized to address both shape and spatial relationship information to produce high precision and to recall values for detection. Floating peak and valleys of projection profiles are used to cut the license plates into individual characters. A turning function-based method is proposed to quickly and accurately recognize each character. It is further accelerated using curvature histogram-based support vector machine. The INFTY dataset is used to train the recognition system, and MediaLab license plate dataset is used for testing. The proposed system achieved 89.45% F-measure for detection and 87.33% accuracy for overall recognition rate which is comparable to current state-of-the-art systems.
© 2015 SPIE and IS&T 1017-9909/2015/$25.00 © 2015 SPIE and IS&T
Siyu Zhu, Sohail A. Dianat, and Lalit K. Mestha "End-to-end system of license plate localization and recognition," Journal of Electronic Imaging 24(2), 023020 (26 March 2015). https://doi.org/10.1117/1.JEI.24.2.023020
Published: 26 March 2015
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Cited by 10 scholarly publications.
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