Abstract
License plate segmentation and recognition (LPSR) method is proposed for Chinese vehicles. The main process of LPSR is divided into three steps: vehicle license plate detection, character segmentation and character recognition. A simple algorithm, local binary pattern histogram (LBPH) is used for vehicle color license plate detection. For segmentation, connected components (CC) algorithm is used. The proposed algorithms have two advantages. First, if the Chinese character of a vehicle plate consists of only one connected stroke/part, the method segments the vehicle plate into required eight characters as Chinese standard license vehicle plate has eight characters (mostly one Chinese character, two/three English alphabets, three/four digits and a dot at third place). Secondly, if Chinese character has more than one stroke/part then this algorithm merges those strokes into one character. For recognition of license plate, support vector machine (SVM) is used. The results of proposed work demonstrate that license plate detection and segmentation methods perform better in terms of accuracy and performance and achieved accuracy rate of recognition is 96.7%.
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Acknowledgment
This work was supported by the national key research and development plan (No. 2017YFC0840200).
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Khan, A., Jinling, Z., Ahmad, I., Wenhao, H., Ali, M., Ali, B. (2020). Chinese License Plate Segmentation and Recognition Based on Color Detection. In: Wang, Y., Fu, M., Xu, L., Zou, J. (eds) Signal and Information Processing, Networking and Computers. Lecture Notes in Electrical Engineering, vol 628. Springer, Singapore. https://doi.org/10.1007/978-981-15-4163-6_5
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DOI: https://doi.org/10.1007/978-981-15-4163-6_5
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