A Hybrid KNN-SVM Model for Iranian License Plate Recognition

This study presents a new method for Iranian License plate recognition systems that will increase the accuracy and decrease the costs of the recognition phase of these systems. In this regard, ahybrid of the k-Nearest Neighbors algorithmand the Multi-Class Support Vector Machines (KNN-SVM) model was developedin the study. K-NN was used as the first classification model as it is simple, robust against noisy data set and effective fora large data set. The confusion among the license plate similar characters problem was overcome by using the multiple SVMs classification model. The SVMs model has improved the performance of the K-NN in the recognition of similar characters. The current study experimental results revealed that there is a significant improvement in the character recognition phase rate compared with a similar study.

[1]  Lakmal D. Seneviratne,et al.  A sensor guided autonomous parking system for nonholonomic mobile robots , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[2]  Seyed Hamidreza Mohades Kasaei,et al.  Extraction and Recognition of the Vehicle License Plate for Passing under Outside Environment , 2011, 2011 European Intelligence and Security Informatics Conference.

[3]  Jin Hyung Kim,et al.  Color Texture-Based Object Detection: An Application to License Plate Localization , 2002, SVM.

[4]  Amir Masoud Rahmani,et al.  Enhancing automatic speed estimation systems performance using support vector machines , 2009, 2009 IEEE 5th International Conference on Intelligent Computer Communication and Processing.

[5]  Jiří Matas,et al.  Unconstrained licence plate and text localization and recognition , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..

[6]  Bartosz Wawrzyniak,et al.  License plate localization and recognition in camera pictures , 2002 .

[7]  Mei Yu,et al.  An approach to Korean license plate recognition based on vertical edge matching , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[8]  Yok-Yen Nguwi,et al.  Two-tier self-organizing visual model for road sign recognition , 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

[9]  Zhang Jianjun,et al.  Research on mutual interference evaluation method of global navigation satellite system , 2013, 2013 IEEE International Conference on Information and Automation (ICIA).

[10]  Yok-Yen Nguwi,et al.  Detection and classification of road signs in natural environments , 2008, Neural Computing and Applications.

[11]  Xiaolei Yu,et al.  Key techniques for multi-satellite integrated navigation system modeling and controlling , 2008, 2008 2nd International Symposium on Systems and Control in Aerospace and Astronautics.

[12]  Shahidan M. Abdullah,et al.  Advantage and drawback of support vector machine functionality , 2014, 2014 International Conference on Computer, Communications, and Control Technology (I4CT).

[13]  Biao Lei,et al.  The optimum configuration of car parking guide system based on wireless sensor network , 2009, 2009 IEEE International Symposium on Industrial Electronics.

[14]  Y. Y. Nguwi,et al.  Number plate recognition in noisy image , 2015, 2015 8th International Congress on Image and Signal Processing (CISP).

[15]  Sei-Wang Chen,et al.  Automatic license plate recognition , 2004, IEEE Transactions on Intelligent Transportation Systems.

[16]  Silvio Savarese,et al.  Comparing image classification methods: K-nearest-neighbor and support-vector-machines , 2012 .

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

[18]  Jianye Liu,et al.  Augmentation of XNAV System to an Ultraviolet Sensor-Based Satellite Navigation System , 2009, IEEE Journal of Selected Topics in Signal Processing.

[19]  Mohammad Pooyan,et al.  Efficient Farsi license plate recognition , 2009, 2009 7th International Conference on Information, Communications and Signal Processing (ICICS).

[20]  Cleber Zanchettin,et al.  A MLP-SVM hybrid model for cursive handwriting recognition , 2011, The 2011 International Joint Conference on Neural Networks.

[21]  Saeed Mozaffari,et al.  Farsi/Arabic Handwritten from Machine-Printed Words Discrimination , 2012, 2012 International Conference on Frontiers in Handwriting Recognition.

[22]  Gaurav Kumar,et al.  A Detailed Review of Feature Extraction in Image Processing Systems , 2014, 2014 Fourth International Conference on Advanced Computing & Communication Technologies.

[23]  Petros A. Ioannou,et al.  Intelligent parking assist , 2013, 21st Mediterranean Conference on Control and Automation.

[24]  S. Imandoust,et al.  Application of K-Nearest Neighbor (KNN) Approach for Predicting Economic Events: Theoretical Background , 2013 .

[25]  Ioannis Anagnostopoulos,et al.  A License Plate-Recognition Algorithm for Intelligent Transportation System Applications , 2006, IEEE Transactions on Intelligent Transportation Systems.

[26]  Fiaz Hussain,et al.  A fast recognition system for isolated arabic characters , 2002, Proceedings Sixth International Conference on Information Visualisation.

[27]  Yok-Yen Nguwi,et al.  Automatic Road Sign Recognition Using Neural Networks , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.