EN
Vehicle Detection Using Fuzzy C-Means Clustering Algorithm
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
References
- T. Sufi,”A Case Study on Market Segmentation, Positioning and Classification of Multi-Brand Hotel Chains”, Emerging Dynamics of Indian Tourism and Hospitality, 2018, 87-97.
- O. Ozdemir, and A. Kaya,”Effect of parameter selection on fuzzy clustering”. Mehmet Akif Ersoy University Applied Scince Journal, vol. 2, pp. 22-33, 2018.
- M. M. Chi, Q. Qian Q., and J. A. Benediktsson “Cluster-based ensemble classification for hyperspectral remote sensing”, in Proc. IEEE IGARSS, 2018, 209–212.
- P. Kamavisdar, et al., “A Survey on Image Classification Approaches and Techniques”, International Journal of Advanced Research in Computer and Communication Engineering, vol. 2, Issue 1, 2008.
- J. C. Bezdek, “Pattern recognition with fuzzy objective function algorithms: Plenum”, New York, 1982, pp. 256.
- D. L. Pham, J. L. Prince, “Adaptive Fuzzy Segmentation of Magnetic Resonance Images”, IEEE Trans. Medical Imaging, vol. 18, pp. 737–752, 1999.
- N. Dhanachandra, K. Manglem and Y. J. Chanu, “Image segmentation using k-means clustering algorithm and subtractive clustering algorithm”, Procedia Computer Science, vol.54, pp.764-771, 2015.
- C. Ambroise, G. Govaert, “Convergence of an EM-type algorithm for spatial clustering”, Pattern Recognition Letters vol. 19, pp. 919–927, 1998.
Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Publication Date
October 1, 2020
Submission Date
September 24, 2020
Acceptance Date
September 30, 2020
Published in Issue
Year 2020 Volume: 8 Number: 3
APA
Saraçoğlu, R., & Nemati, N. (2020). Vehicle Detection Using Fuzzy C-Means Clustering Algorithm. International Journal of Applied Mathematics Electronics and Computers, 8(3), 85-91. https://doi.org/10.18100/ijamec.799431
AMA
1.Saraçoğlu R, Nemati N. Vehicle Detection Using Fuzzy C-Means Clustering Algorithm. International Journal of Applied Mathematics Electronics and Computers. 2020;8(3):85-91. doi:10.18100/ijamec.799431
Chicago
Saraçoğlu, Rıdvan, and Nooshin Nemati. 2020. “Vehicle Detection Using Fuzzy C-Means Clustering Algorithm”. International Journal of Applied Mathematics Electronics and Computers 8 (3): 85-91. https://doi.org/10.18100/ijamec.799431.
EndNote
Saraçoğlu R, Nemati N (October 1, 2020) Vehicle Detection Using Fuzzy C-Means Clustering Algorithm. International Journal of Applied Mathematics Electronics and Computers 8 3 85–91.
IEEE
[1]R. Saraçoğlu and N. Nemati, “Vehicle Detection Using Fuzzy C-Means Clustering Algorithm”, International Journal of Applied Mathematics Electronics and Computers, vol. 8, no. 3, pp. 85–91, Oct. 2020, doi: 10.18100/ijamec.799431.
ISNAD
Saraçoğlu, Rıdvan - Nemati, Nooshin. “Vehicle Detection Using Fuzzy C-Means Clustering Algorithm”. International Journal of Applied Mathematics Electronics and Computers 8/3 (October 1, 2020): 85-91. https://doi.org/10.18100/ijamec.799431.
JAMA
1.Saraçoğlu R, Nemati N. Vehicle Detection Using Fuzzy C-Means Clustering Algorithm. International Journal of Applied Mathematics Electronics and Computers. 2020;8:85–91.
MLA
Saraçoğlu, Rıdvan, and Nooshin Nemati. “Vehicle Detection Using Fuzzy C-Means Clustering Algorithm”. International Journal of Applied Mathematics Electronics and Computers, vol. 8, no. 3, Oct. 2020, pp. 85-91, doi:10.18100/ijamec.799431.
Vancouver
1.Rıdvan Saraçoğlu, Nooshin Nemati. Vehicle Detection Using Fuzzy C-Means Clustering Algorithm. International Journal of Applied Mathematics Electronics and Computers. 2020 Oct. 1;8(3):85-91. doi:10.18100/ijamec.799431
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