近幾年車牌自動化辨識系統在停車場收費或交通違規取締上被廣泛的研究與發展，本篇論文提出一套以FPGA實現之即時車牌辨識系統，並加入車牌偵測流程處理步驟的硬體模組加入SOPC系統平台上，同時達到即時偵測的效能。本篇論文在車牌偵測演算法步驟上，主要以離散小波演算法與型態學完成車牌定位，再利用物件連通法，準確的分辦出每一獨立區塊，並找出影像中車牌位置座標點，再將車牌區域內之字元分割出來，得到車牌中每一字元座標點後，最後將字元影像傳送至字元辨識軟體(OCR)，完成車牌字元辨識。
利用上述演算流程方法，我們可以將此構想實現於友晶科技DE2-70 FPGA實驗板上，並以Altera NIOS II嵌入式軟核心處理器及SOPC平台為開發環境，結合攝影機當作影像來源，系統使用像素設定為720X487，並將系統在偵測到車牌位置和成功切割出字元的畫面時，透過VGA輸出影像，顯示在Monitor上。
最後，在既定條件下，距離車體1~3公尺、車牌傾斜不超過5度、車牌區域內無明顯毀損或髒污下，我們可以成功擷取出車牌達96%而字元切割成功率也達到85%。如果在未設限外在環境和影像中車牌位置的情形下，即使原始影像有些許傾斜或有不同強度光線照射，經實驗證實，我們可以得到約80.5%的成功車牌偵測率。

In recent years, research and development of automated license plate recognition system in terms of car parking charges or traffic ban. this paper presents the implementation of a real-time FPGA license plate recognition system, and we achieve the detect license detection plate hardware base on SOPC, we got good performance of real-time detection .In this paper, the license plate detection we achieve by using discrete wavelet transform(DWT) and morphology. Furthermore the object Connect Component Labeling method to segment each independent block and identify the images license plate location coordinates. Before we get the characters of each registration coordinates, we should segment each region of the characters from the plate. The character image will be send to character recognition software (OCR). After that, the license plate characters identification will be finish.
Using above method, we can achieve this purpose on Terasic company’s DE2-70 FPGA development kit, which compose of Altera NIOS II soft core embedded processor and SOPC platform development environment. And it combined with camera whose resolution is 720X487.After the system finished the plate detection and cutting out characters, it shows the result from VGA interface to the Monitor.
Finally, we can successfully capture the license plate on the rate 96% and 85% on segment the characters, the constrained of our environment are the following: the vehicle 1 to 3 meters, the license plate can’t slope over 5 degrees, the region had no any obviously shelters or dust. If on the other environment, even if the original image slightly tilted or have different light intensity. According to the experiment, we can still reach 80.5% success rate of license plate detection.

[1] Hakan Caner, H. Selcuk Gecim, and Ali Ziya Alkar, “Efficient Embedded Neural-Network-Based License Plate Recognition System,” IEEE Transactions on Vehicular Technology, Vol. 57, Issue 5, pp. 2675 – 2683(2008).
[2] 吳國修，「基於離散小波轉換與形態學硬體實現多個車牌偵測」，碩士論文，國立台灣科技大學，台北(2008)。
[3] 楊汝浩，「汽車牌照識別」，碩士論文，國立交通大學，新竹，民國75年。
[4] S.-Z. Wang and H.-J. Lee, “Detection and recognition of license plate characters with different appearances,” 2003 IEEE Proceedings Intelligent Transportation Systems, Vol. 2, PP. 979-984(2003).
[5] S. Kim, D. Kim, Y. Ryu, and G. Kim, “A robust license-plate extraction method under complex image conditions,” Proceedings of 16th International Conference on Pattern Recognition, Vol. 3, pp. 216-219(2002).
[6] Haidong Fu, Mei Xie, “Design and realization of license plate recognition system based on DSP and FPGA,” 2008 IEEE International Symposium on IT in Medicine and Education, PP. 39 – 43(2008).
[7] ZeWei Liu, HaiDong Fu, Mei Xie, “Multiple Processors License Plate Recognition System for Intelligent Transportation Management,” 2008 Second International Symposium on Intelligent Information Technology Application, Vol. 1, pp. 333 – 336(2008).
[8] Mei Xie, Haidong Fu, Zewei Liu, “One design method of license plate recognition system with high recognition rate,” 2008 IEEE International Symposium on IT in Medicine and Education, pp. 44 – 49(2008).
[9] Takamasa Kanamori, Hideharu Amano, Masatoshi Arai, Yoshiaki Ajioka, “A HIGH SPEED LICENSE PLATE RECOGNITION SYSTEM ON AN FPGA,“2007 International Conference on Field Programmable Logic and Applications, pp. 554 – 557(2007).
[10] Nikolaos Bellas, Sek M. Chai, Malcolm Dwyer, Dan Linzmeier, “FPGA implementation of a license plate recognition SoC using automatically generated streaming accelerators,“ 2006 20th International Parallel and Distributed Processing Symposium, pp. 567-572(2006).
[11] 李志文，「嵌入式即時多標的汽機車牌照辨識系統」，碩士論文，國立台灣科技大學, 台北(2008)。
[12] Eun Ryung Lee, Pyeoung Kee Kim, and Hang Joon Kim, “AUTOMATIC RECOGNITION OF A CAR LICENSE PLATE USLNG COLOR IMAGE PROCESSING,” Proceedings of the IEEE International Conference Image Processing, vol.2, pp. 301 – 305(1994).
[13] K. Gengi, ''A Method for Character Region Extraction in Automatic Vehicle dentiffcation Device,'' Proc. Annual Conf. IECE, pp. 1352-1357(1986).
[14] Paolo Castello, Christopher Coelho, Enrico Del Ninno, Ennio Ottaviani, Michele Zanini, ”Traffic monitoring in motorways by real-time number plate recognition,” Proceedings of International Conference on Image Analysis and Processing, pp. 1128 – 1131(1999).
[15] Guangmin SUN, Gang LI, Lei XU, Jing WANG, ''A new method of vehicle license plate location based on mathematical morphology and texture characteristics,” 2008 3rd IEEE Conference on Industrial Electronics and Applications, pp. 985 – 988(2008).
[16] Farhad Faradji, Amir Hossein Rezaie, Majid Ziaratban, ''A Morphological-Based License Plate Location,” 2007 IEEE International Conference on Image Processing, Vol.1, pp. 57– 60(2007).
[17] Haibin Huang, Guangfu Ma, Yufei Zhuang, ''Vehicle license plate location based on Harris corner detection,'' IEEE International Joint Conference on Neural Networks, pp. 352 – 355(2008).
[18] Feng Yang, Zheng Ma, ''Vehicle license plate location based on histogramming and mathematical morphology,'' Fourth IEEE Workshop on Automatic Identification Advanced Technologies, pp. 89 – 94(2005).
[19] L. Dlagnekovin , ''License Plate Detection Using AdaBoost,'' La Jolla: Comput. Sci. Eng. Dept., Univ. California San Diego, Mar. 2004.[Online]. http://www.cse.ucsd.edu/classes/fa04/cse252c/projects/louka.pdf
[20] Ruili Zeng, Gang Li, Yunkui Xiao, Mengjun Wang, ''Algorithm of car license plates location based on multi-feature fusion,'' 2008 7th World Congress on Intelligent Control and Automation, pp. 8483 – 8486(2008).

[21] Guangying Ge, Jianjian Xu, Minghong Wang, ''On the Study of Image Characters Location, Segmentation and Pattern Recognition using LS-SVM,'' 2006 The Sixth World Congress on Intelligent Control and Automation, Vol. 2, pp. 9650 – 9654(2006).
[22] Sweldens, “The Lifting Scheme: A Custom Design and Contruction of Biorthogonal Wavelets,” Appiled and Computational Harmonic Analysis (ACHA), pp.186-200( 1996).
[23] Bai Hongliang, Liu Changping, “A hybrid license plate extraction method based on edge statistics and morphology,” 2004 Proceedings of the 17th International Conference on Pattern Recognition, Vol. 2, pp. 831 – 834(2004).
[24] Jose Oliver, Elena Oliver, Manuel P. Malumbres, “Fast Integer-to-Integer Reversible Lifting Transform with Reduced Memory Consumption,” 2005 Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, pp. 289 – 294(2005).
[25] Analog Device,"ADSP-BF533 Blackfin Processor Hardware Reference", Preliminary Revision (2003).
[26] 呂炎州，「不需字元切割的車牌辨識法」，碩士論文，靜宜大學資訊管理學研究所,台中(2003)。
[27] Cheokman Wu, Lei Chan On, Chan Hon Weng, Tong Sio Kuan, Kengchung Ng, “A Macao license plate recognition system,” Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vol. 7, pp. 4506 – 4510(2005).
[28] Feng Yang, Zheng Ma, Mei Xie, “A Robust Character Segmentation Approach for License Plate,” 2007 International Conference on Communications, Circuits and Systems, pp. 679 – 683(2007).
[29] Y. Lu, “On the Segmentation of Touching Characters,” Proceedings of the Second International Conference on Document Analysis and Recognition, pp. 440-443(1993).
[30] 官宗，「利用數位訊號處理器實現車牌字元辨識系統」，碩士論文，國立台灣大學電機工程學研究所，台北，民國90年。
[31] Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, 2nd Edition, Prentice-Hall, New Jersey, (2002).
[32] Ito, Y., Nakano, K.,” Component labeling for k-concave binary images using an FPGA,” 2008 IEEE International Symposium on Parallel and Distributed Processing, pp. 1 – 8(2008).
[33] J. R. Parker, Algorithms for Image Processing and Computer Vision, Wiley, (1996).