An Iterative Growing and Pruning Algorithm for Classification Tree Design
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method of Combining Multiple Experts for the Recognition of Unconstrained Handwritten Numerals
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A structural/statistical feature based vector for handwritten character recognition
Pattern Recognition Letters
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A novel feature extraction method and hybrid tree classification for handwritten numeral recognition
Pattern Recognition Letters
Character Recognition by Geometrical Moments on Structural Decompositions
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Probabilistic Framework for Combining Multiple Classifiers at Abstract Level
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Color Texture-Based Object Detection: An Application to License Plate Localization
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
Automatic license extraction from moving vehicles
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
Preceding vehicle recognition based on learning from sample images
IEEE Transactions on Intelligent Transportation Systems
Data mining for decision support in multiple-model system identification
SMO'06 Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization
Real-Time Car License Plate Recognition Improvement Based on Spatiognitron Neural Network
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
A combined statistical-structural strategy for alphanumeric recognition
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
A neuro-fuzzy inference engine for Farsi numeral characters recognition
Expert Systems with Applications: An International Journal
Analysis of four polar shape descriptors properties in an exemplary application
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part I
Car plate recognition by whole 2-D image
Expert Systems with Applications: An International Journal
Combining two data mining methods for system identification
EG-ICE'06 Proceedings of the 13th international conference on Intelligent Computing in Engineering and Architecture
Zoning methods for handwritten character recognition: A survey
Pattern Recognition
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Image-based car plate recognition is an indispensable part of an intelligent traffic system. The quality of the images taken for car plates, especially for Chinese car plates, however, may sometimes be very poor, due to the operating conditions and distortion because of poor photographical environments. Furthermore, there exist some ''similar'' characters, such as ''8'' and ''B'', ''7'' and ''T'' and so on. They are less distinguishable because of noises and/or distortions. To achieve robust and high recognition performance, in this paper, a two-stage hybrid recognition system combining statistical and structural recognition methods is proposed. Car plate images are skew corrected and normalized before recognition. In the first stage, four statistical sub-classifiers recognize the input character independently, and the recognition results are combined using the Bayes method. If the output of the first stage contains characters that belong to prescribed sets of similarity characters, structure recognition method is used to further classify these character images: they are preprocessed once more, structure features are obtained from them and these structure features are fed into a decision tree classifier. Finally, genetic algorithm is employed to achieve optimum system parameters. Experiments show that our recognition system is very efficient and robust. As part of an intelligent traffic system, the system has been in successful commercial use.