Research and Design of the License Plate Recognition Systems Based on ARM S3C2440

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Abstract:

In order to meet the need of real-time and dynamic monitoring of intelligent transportation, a License Plate Recognition (LPR) System Based on ARM S3C2440 is introduced and a vehicle license recognition system is designed and realized. This thesis comparatively explains the tasks and problems and dose analytic research across all phases of the system. Image binary and slant rectification also be discussed, which are difficulty points in LPR. According to the study of the license plate images, we use hough transformation and image reverse rotation , a inclined rectification method was proposed. The experimental results show that the approach is excellent in the accuracy with rapid speed and is in the robustness.

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2484-2488

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July 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Li Gang, Yuan Rongdi, Yang Zuyuan, el. A yellow .license plate location method based on RGB model of color image and texture of plate[C]/Proceedings of the Second Workshop on digital Media and Its Application in Museum&heritages. Chongqing China. 2007: 42_46.

DOI: 10.1109/dmamh.2007.35

Google Scholar

[2] Hallinan C. Embedded Linux Primer[M]. America: Prentice Hall PTR. (2006).

Google Scholar

[3] Michael H Schimek. Video for Linux for Linux Two API Specification [EB/OL]. HTTP: /v412specbytesex. org. /v412spec/v412. pdf, 2008-0304.

Google Scholar

[4] Ji Wangkang, Yang Jia, Hong Yongqiang. BSP development of Linux system for vehicle navigation device based on s3c2440[J]. Electronic measurement and Instruments, 8th Internetional conference, 2007: 389-391.

DOI: 10.1109/icemi.2007.4350699

Google Scholar

[5] FINLAYSON G D, HORDLEY S D, LU Cheng, et al. On the removal of shadows from images[J]. IEEE Transactions on pattern Analysis and Machine Intelligence, 2006, 28(1): 59-68.

DOI: 10.1109/tpami.2006.18

Google Scholar

[6] Gu Lixu, Kanakan, Tanaka, eta1.Ro—bust Extraction of Characters from Color Scene Image Using M athemati—cal Morphology.IEEE, 2000.

Google Scholar