JOURNAL ARTICLE

Vehicle Detection Using Fuzzy C-Means Clustering Algorithm

Rıdvan SaraçoğluNooshin Nemati

Year: 2020 Journal:   International Journal of Applied Mathematics Electronics and Computers Vol: 8 (3)Pages: 85-91

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:
Cluster analysis Identification (biology) Artificial intelligence Image (mathematics) Computer science Field (mathematics) Data mining Pattern recognition (psychology) Support vector machine Fuzzy logic Function (biology) Fuzzy clustering Image segmentation Property (philosophy) Mathematics

Metrics

5
Cited By
0.60
FWCI (Field Weighted Citation Impact)
16
Refs
0.75
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Vehicle License Plate Recognition
Physical Sciences →  Engineering →  Media Technology
Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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