影像處理及類神經乏晰於車輛牌照自動辨識之應用研究

A Hybrid Approach for Automatic Vehicle License Plate Recognition

仲崇實

汽車牌照自動辨識 ； 樣式辨認 ； 光學字元閱讀 ； 類神經網路 ； Vehicle License Plate Recognition ； Pattern Recognition ； OCR ； Neural Network

元智大學資訊研究所學位論文

1997年

碩士

李 錫 捷

繁體中文

一般傳統的車輛辨識系統，多半使用了R.F.、microwave或紅外線等技術來進行辨認，並且透過在車輛上安裝的transponder，將資料傳送給感測設備。這樣的系統在實施時，必須顧慮到transponder必須安裝在所有車輛上的成本問題以及其故障的可能性。 在本研究中，我們提出了一個混合方法，用以對於車輛牌照進行自動的辨認，並且建立了一個雛形系統，可以獨立作業或是與其他現有的車輛辨識系統合作處理。本系統大致可以分成四個主要的模組，它們分別是：牌照定位模組－負責由影像中找出概略的牌照位置、字元擷取與正規化模組－由牌照影像中，取出各個字元，並且正規化、辨識模組－專司辨識各個已經分離出來的字元，以及SimNet類神經－乏晰系統模組。 為了驗證此系統的效能，我們以數位照相機蒐集了417張影像，經由實驗結果得知，本系統的牌照正確率約在93.5%，而字元辨識的正確率為97.3%。

Most currently available vehicle identification systems use techniques such as R. F., microwave, or infrared to help identifying the vehicle. Transponders are usually installed in the vehicle in order to transmit the corresponding information to the sensory systems. It is considered expensive to install a transponder in each vehicle and malfunction of the transponder will result in the failure of the vehicle identification system. In this study, a hybrid approach is proposed for automatic vehicle license plate recognition. A system prototype is built which can be used independently or cooperating with current vehicle identification system in identifying a vehicle. The prototype consists of four major modules including the module for license plate region identification, the module for character extraction from the license plate, the module for character recognition, and the module for pattern recognition using SimNet. To test the performance of the proposed system, 417 vehicle image samples are using by a digital camera. The license plate recognition success rate of the prototype is 93.5% while the character recognition success rate of the prototype is 97.3%

1. 2. Kenji Kanayama, Yoshimasa Fujikawa, Koichi Fujimoto and Masanobu Horino, “Development of vehicle-license number recognition system using real-time image processing and its application to travel-time measurement,” The 41st IEEE VEHICULAR TECHNOLOGY CONFERENCE 1991, pp. 798-804, 1991
   連結：
2. 5. J.R. Cowell, “Syntactic pattern recognizer for vehicle identification numbers,” Image and Vision Computing, Vol.13, No.1, pp. 13-19, 1995.
   連結：
3. 7. J. Serra, Image Analysis and Mathematical Morphology, Academic Press, New York, 1982.
   連結：
4. 8. J.R. Parker, Algorithms for Image Processing and Computer Vision, Wiley, New York, 1996.
   連結：
5. 9. N. Otsu,”A threshold selection method from gray-level histo-grams,” IEEE Transaction on Systems, Man, and Cybernetics, Vol. SMC-9, pp.62-66, 1979.
   連結：
6. 10. J.-G. Leu, “Shape normalization through compacting,” Pattern Recognition Letters, Vol. 10, No. 4, pp.243-250, 1989.
   連結：
7. 11. Soo-Chang Pei, Chao-Nan Lin, “Image normalization for pattern recognition,” Image and Vision Computing, Vol.13, No. 10, pp.711-723, 1995.
   連結：
8. 12. D. Cyganski and J.A. Orr, “Application of tensor theory to object recognition and orientation determination,” IEEE Trans. PAMI, Vol. 7, No. 6, pp.662-673, 1985.
   連結：
9. 13. Barroso J, Bulas-Cruz J and Dagless E L, “Real-Time Number Plate Reading,” 4th IFAC Workshop on Algorithms and Architectures for Real-time Control, Vilamoura, Portugal, April 1997.
   連結：
10. 14. Dai Ying, Zheng Nanning, Zhang Xining and Xuan Guorong, “Automatic recognition of province name on the license plate of moving vehicle,” 9th International Conference on Pattern Recognition, Vol. 2, pp.927-929, 1988.
    連結：
11. 15. Kenji Kanayama, Yoshimasa Fujikawa and Koichi Fujimoto, “Development and Application of Vehicle-License Number Recognition System Using Real-Time Image Processing,” Systems and Computers in Japan, Vol. 22, No. 1, pp.1723-1729, 1991.
    連結：
12. 16. F. Lisa, J.Carrabina, C. Perez-Vicente, N. Avellana and E. Valderrama, “Two-bit weights are enough to solve vehicle license number recognition problem,” 1993 IEEE International Conference on Neural Networks, Vol. 3, pp.1242-1246, 1993.
    連結：
13. 17. Eun Ryung Lee, Pyeoung Kee Kim and Hang Joon Kim, “Automatic recognition of a car license plate using color image processing,” Proceedings ICIP-94, Vol. 2, pp.301-305, 1994.
    連結：
14. 18. Maged M.M. Fahmy, “Automatic number-plate recognition: neural network approach,” 1994 Vehicle Navigation and Information Systems Conference Proceedings, pp.99-101, 1994.
    連結：
15. 26. Bart Kosko, Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence, Prentice-Hall, pp.263-298,1992.
    連結：
16. 1. K.Waersted, “Automatic toll ring no stop electronic payment systems in Norway -systems layout and full scale experiences,” Sixth International Conference on Road traffic Monitoring and Control, pp.16-23, 1992
17. 3. Paolo Comelli, Paolo Ferragina, Mario Notturno Granieri and Flavio Stabile, “Optical recognition of motor vehicle license plates,” IEEE Transactions on Vehicular Technology, Vol. 44, No. 4, pp. 790-799, 1995.
18. 4. Joe C.H. Poon, Muffaddal Ghadiali, Gray M.T. Man and Lau Man Sheung, “A robust vision system for vehicle licence plate recognition using grey-scale morphology,” ISIE’95 Proceedings of the IEEE International Symposium on Industrial Electronics, Vol.1, pp. 394-399, 1995.
19. 6. Ramesh Jain, Rangachar Kasturi and Brian G. Schunck, Machine Vision, McGraw-Hill, New York, 1995.
20. 19. J.A.G. Nijhuis, M.H. ter Brugge, K.A. Helmholt, J.P.W. Pluim, L. Spaanenburg, R.S. Venema and M.A. Westenberg, “Car license plate recognition with neural networks and fuzzy logic,” 1995 IEEE International Conference on Neural Networks Proceedings, Vol.5, pp. 2232-6, 1995.
21. 20. R.A. Lotufo, A.D. Morgan and A.S. Johnson, “Automatic number-plate recognition,” IEE Colloquium on ''Image Analysis for Transport Applications'' (Digest No.035),pp. 6/1-6, 1990.
22. 21. D. Enke, H. C. Lee, A. M. Ozbayoglu, A. Thammano, and C. H. Dagli, “An Application to Speaker Identification Using SimNet”, Intelligence Engineering Systems Through Artificial Neural Networks, vol. 5, ASME Press (ANNIE’95), New York, 1995.
23. 22. 楊文宗, “車輛牌照號碼自動辨識系統”, 私立中原大學電子工程研究所,碩士論文, 1996六月
24. 23. 周俊男, ”車輛牌照影像辨識系統”, 國立中山大學資訊工程研究所, 碩士論文，1995六月
25. 24. 張銘豪, “利用分割辨識方法之英文數字辨識系統”, 國立中山大學資訊工程研究所, 碩士論文，1996七月
26. 25. K. Tanabe, E. Marubayashi, H. Kawashima, T. Nakanishi and A. Shio, “PC-Based Car License Plate Reading,” Image and Video Processing II, SPIE Vol.2182, pp.220-231, 1994

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