Vehicle Detection Using Fuzzy C-Means Clustering Algorithm

Year 2020, , 85 - 91, 01.10.2020

Rıdvan Saraçoğlu , Nooshin Nemati

https://doi.org/10.18100/ijamec.799431

Cited By: 4

Abstract

Vehicle detection and identification are very important functions in the field of traffic control and management. Generally, a study should be conducted on big data sets and area characteristics to get closer to this function. The aim is to find the most appropriate model for these data. Also, the model that is prepared for the data aims to recognize the factors on the image. In other words, it aims to assign factors to the right classes and differentiate them. A classification of the image is made in that way. In this study, a vehicle identification system, in which Fuzzy C-Means Algorithm is used for image segmentation and the Support Vector Machine is used for image classification, is presented. The currentness of these methods is their most important property. The obtained results show that the selected methods are applied successfully and effectively.

Keywords

Clustering, Fuzzy C Means, Support Vector Machine, Vehicle Identification

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