Abstract
A robust method for plate segmentation in a License Plate Recognition system is presented in this paper, the proposed approach is designed to work in a wide range of acquisition conditions, including unrestricted scene environments, lighting conditions, viewing points and camera-to-car distance. Experiments have been preformed to prove the robustness and accuracy of the approach. The experiment results show that almost 96.2% of input images are correctly segmented on the average. Because our algorithm has fast speed and needs little memory space, it can be used in real time system.
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© 2005 Springer-Verlag Berlin Heidelberg
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Kong, J., Liu, X., Lu, Y., Zhou, X., Zhao, Q. (2005). Robust License Plate Segmentation Method Based on Texture Features and Radon Transform. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_53
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DOI: https://doi.org/10.1007/11589990_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30462-3
Online ISBN: 978-3-540-31652-7
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