Procedia Computer Science 102 (2016) 588 – 594 1877-0509 © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the Organizing Committee of ICAFS 2016 doi:10.1016/j.procs.2016.09.447 ScienceDirect Available online at www.sciencedirect.com 12th International Conference on Application of Fuzzy Systems and Soft Computing, ICAFS 2016, 29-30 August 2016, Vienna, Austria A hybrid KNN-SVM model for Iranian license plate recognition Sahar S. Tabrizi a *, Nadire Cavus a a Department of Computer Information Systems, Near East University, P.O.BOX:99138, Nicosia, North Cyprus, Mersin 10, Turkey. Abstract 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. © 2016 The Authors. Published by Elsevier B.V. Peer-review under responsibility ofthe Organizing Committee of ICAFS 2016. Keywords:KNN-SVM Hybrid Model; Machine Learning; Image Processing; Iranian License Plate Recognition; Feature Extraction; 1. Introduction Lookingat our daily lives, we canfind the footprints of improving computer science and engineering in every aspect of life such as education, tourism, health and transportation. One of the most rapidly developing areas in the field of engineering is that of Intelligent Transformation System (ITS) 1 . ITS, as an active research area, has started to play an important role in people’s lives such as in transport and mobility safety 2 . This phenomenon has encouraged governments and the private sector alike to exploit advanced technologies 3 . Satellite system navigation 4,5,6 , road sign automatic recognition 7,8,9 guided parking systems 10,11,12 , license plate recognition 13,14,15 and vehicular security 1 are some of the various ITS types. * Sahar S. Tabrizi; Tel.: +90-392-675-1000. E-mail address: sahar.shokouhi@neu.edu.tr © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the Organizing Committee of ICAFS 2016