Abstract
With the development of Intelligent Transport Systems (ITS), automatic license plate recognition (LPR) plays an important role in numerous applications in reality. In this paper, a coarse to fine algorithm to detect license plates in images and video frames with complex background is proposed. First, the method based on Component Connect (CC) is used to detect the possible license plate regions in the coarse detection. Second, the method based on texture analysis is applied in the fine detection. Finally, a BP Neural Network is adopted as classifier, parts of the features is selected based on statistic diagram to make the network efficient. The average accuracy of detection is 95.3% from the images with different angles and different lighting conditions.
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© 2007 Springer Berlin Heidelberg
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Li, Y., Li, M., Lu, Y., Yang, M., Zhou, C. (2007). A New Text Detection Approach Based on BP Neural Network for Vehicle License Plate Detection in Complex Background. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_101
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DOI: https://doi.org/10.1007/978-3-540-72393-6_101
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72392-9
Online ISBN: 978-3-540-72393-6
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