Extracting characters from real vehicle licence plates out-of-doors

Most applications of automatic vehicle identification systems are outdoors and are consumer-orientated. The recognition rate, the system reliability and the processing speed are very important. A system for extracting characters from licence plates has been presented. The system can successfully extract characters from licence plates in any part of a captured image without the need to consider the luminance of the surroundings or the size and inclination of the licence plate or the colour of the vehicle. Moreover, the processing time of this system is satisfactory for several applications. The proposed system depends only on the completeness of a character and so is tolerant of skewed plates and complex backgrounds. In a real parking lot, an extraction rate of 95.6% was obtained by applying the system to 228 vehicles.

[1]  Paolo Ferragina,et al.  Optical recognition of motor vehicle license plates , 1995 .

[2]  Dashan Gao,et al.  Car license plates detection from complex scene , 2000, WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000.

[3]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Liu Ning,et al.  Translation, Rotation and Scale-Invariant Object Recognition , 2001 .

[5]  J. Barroso,et al.  Number plate reading using computer vision , 1997, ISIE '97 Proceeding of the IEEE International Symposium on Industrial Electronics.

[6]  Kenji Kanayama,et al.  Development of vehicle-license number recognition system using real-time image processing and its application to travel-time measurement , 1991, [1991 Proceedings] 41st IEEE Vehicular Technology Conference.

[7]  Anil K. Jain,et al.  Introduction to Pattern Recognition , 2007 .

[8]  Kwang In Kim,et al.  Learning-based approach for license plate recognition , 2000, Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501).

[9]  Alan L. Harvey,et al.  Car Number Plate Detection With Edge Image Improvement , 1996, Fourth International Symposium on Signal Processing and Its Applications.

[10]  Hang Joon Kim,et al.  A recognition of vehicle license plate using a genetic algorithm based segmentation , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[11]  Kosin Chamnongthai,et al.  The recognition of car license plate for automatic parking system , 1999, ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359).

[12]  Byung Tae Chun,et al.  Design of real time vehicle identification system , 1994, Proceedings of IEEE International Conference on Systems, Man and Cybernetics.

[13]  J. R. Cowell Syntactic pattern recognizer for vehicle identification numbers , 1995, Image Vis. Comput..

[14]  Miha Mraz,et al.  The fuzzy logic approach to the car number plate locating problem , 1997, Proceedings Intelligent Information Systems. IIS'97.

[15]  Wu Wei,et al.  Research on number-plate recognition based on neural networks , 2001, Neural Networks for Signal Processing XI: Proceedings of the 2001 IEEE Signal Processing Society Workshop (IEEE Cat. No.01TH8584).

[16]  Lambert Spaanenburg,et al.  Car license plate recognition with neural networks and fuzzy logic , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[17]  Hanan Samet,et al.  Connected Component Labeling Using Quadtrees , 1981, JACM.

[18]  Slobodan Ribarić,et al.  Introduction to Pattern Recognition , 1988 .

[19]  Azriel Rosenfeld,et al.  Sequential Operations in Digital Picture Processing , 1966, JACM.

[20]  L. De Vena,et al.  Number plate recognition by hierarchical neural networks , 1993 .

[21]  Kenji Suzuki,et al.  Fast connected-component labeling based on sequential local operations in the course of forward raster scan followed by backward raster scan , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[22]  Thurai Vinay,et al.  Hough Transform In Car Number Plate Skew Detection , 1996, Fourth International Symposium on Signal Processing and Its Applications.

[23]  Keiichi Yamada,et al.  Robust license-plate recognition method for passing vehicles under outside environment , 2000, IEEE Trans. Veh. Technol..

[24]  Paolo Castello,et al.  Traffic monitoring in motorways by real-time number plate recognition , 1999, Proceedings 10th International Conference on Image Analysis and Processing.

[25]  Phalguni Gupta,et al.  Finding connected components in digital images , 2001, Proceedings International Conference on Information Technology: Coding and Computing.

[26]  R. Domer,et al.  Feature based recognition of traffic video streams for online route tracing , 1998, VTC '98. 48th IEEE Vehicular Technology Conference. Pathway to Global Wireless Revolution (Cat. No.98CH36151).

[27]  Hang Joon Kim,et al.  Automatic recognition of a car license plate using color image processing , 1994, Proceedings of 1st International Conference on Image Processing.

[28]  Chris J. Harris,et al.  VEHICLE DETECTION AND RECOGNITION IN GREYSCALE IMAGERY , 1995 .

[29]  Qian Huang,et al.  Extracting characters of license plates from video sequences , 1998, Machine Vision and Applications.

[30]  Y. Tanaka Travel-time data provision system using vehicle license number recognition devices , 1992, Proceedings of the Intelligent Vehicles `92 Symposium.