Các nguyên mẫu chiết xuất của năm phương pháp khác nhau đã được sử dụng để khởi tạo codebooks LVQ: phương pháp (1) là việc khai thác nguyên mẫu phương pháp được đề xuất trong chương này. Phương pháp (2) và (3) là hai phương pháp được gọi là propinit và eveninit, đề xuất trong [13] | Experimental Analysis and Results 31 Figure The overall process of an LPR system showing a car and license plate with dust and scratches. Table Recognition rate for license plate extraction license plate segmentation and license plate recognition. License plate extraction License plate segmentation License plate recognition Correct recognition 587 610 574 610 581 610 Percentage recognition 32 License Plate Recognition System 8. Conclusion Although there are many running systems for recognition of various plates such as Singaporean Korean and some European license plates the proposed effort is the first of its kind for Saudi Arabian license plates. The license plate recognition involves image acquisition license plate extraction segmentation and recognition phases. Besides the use of the Arabic language Saudi Arabian license plates have several unique features that are taken care of in the segmentation and recognition phases. The system has been tested over a large number of car images and has been proven to be 95 accurate. References 1 Kim K. K. Kim K. I. Kim J. B. and Kim H. J. Learning based approach for license plate recognition Proceedings ofỉEEE Processing Society Workshop on Neural Networks for Signal Processing 2 pp. 614-623 2000. 2 Bailey D. G. Irecki D. Lim B. K. and Yang L. Test bed for number plate recognition applications Proceedings of the First IEEE International Workshop on Electronic Design Test and Applications DELTA 02 iEeE Computer Society 2002. 3 Hofman Y. License Plate Recognition-A Tutorial Hi-Tech Solutions http whatis 2004. 4 Salgado L. Menendez J. M. Rendon E. and Garcia N. Automatic car plate detection and recognition through intelligent vision engineering Proceedings of IEEE 33rd Annual International Carnahan Conference on Security Technology pp. 71-76 1999. 5 Naito T. Tsukada T. Yamada K. Kozuka K. and Yamamoto S. Robust license-plate recognition method for passing vehicles under
