DETEKSI RODA KENDARAAN DENGAN CIRCLE HOUGH TRANSFORM (CHT) DAN SUPPORT VECTOR MACHINE (SVM)

Sri Dianing Asri, Desi Ramayanti, Ade Dwi Putra, Yohana Tri Utami

Abstract


In the digital image processing, many methods have been developed, the purpose of developing these methods is how computers can detect and recognize objects in an image with a precisely and process them in a relatively short time. Wheels are components that are always present in every vehicle, whether the vehicle is a bus, car or truck, it must have wheels with the same shape. If a wheel can be detected and recognized then the vehicle recognition and classification can be determined. This research focuses on capturing circle images, detecting wheel circles by applying Circle Hough Transformation (CHT). This transformation is able to recognize the object based on its boundaries and is resistant to noise. After obtaining the image of the circle, the next step is to classify it into Wheels and Non Wheels using the Support Vector Machine (SVM) method. The development of the wheel circle detection model on the side view image of this vehicle can be used as one of the first steps in research on wheel-based automatic vehicle recognition and classification systems.


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References


Y. F. Fung, H. Lee, and M. F. Ercan, “Image processing application in toll collection,” Lect. Notes Eng. Comput. Sci., no. April 2015, pp. 584–588, 2006.

M. Hutter and N. Brewer, “Matching 2-D ellipses to 3-D circles with application to vehicle pose identification,” 2009 24th Int. Conf. Image Vis. Comput. New Zealand, IVCNZ 2009 - Conf. Proc., pp. 153–158, 2009, doi: 10.1109/IVCNZ.2009.5378421.

A. Bhujbal and D. Mane, “A survey on deep learning approaches for vehicle and number plate detection,” Int. J. Sci. Technol. Res., vol. 8, no. 12, pp. 1378–1383, 2019.

A. O. Djekoune, K. Messaoudi, and K. Amara, “Incremental circle hough transform: An improved method for circle detection,” Optik (Stuttg)., vol. 133, pp. 17–31, 2017, doi: 10.1016/j.ijleo.2016.12.064.

V. A. Gunawan and L. S. A. Putra, “Comparison of American Sign Language Use Identification using Multi-Class SVM Classification, Backpropagation Neural Network, K - Nearest Neighbor and Naive Bayes,” Teknik, vol. 42, no. 2, pp. 137–148, 2021, doi: 10.14710/teknik.v42i2.36929.

J. Jumadi and D. Sartika, “Pengolahan Citra Digital Untuk Identifikasi Objek Menggunakan Metode Hierarchical Agglomerative Clustering,” vol. 10, no. 2, pp. 148–156, 2021.

A. R. Putri, “Pengolahan Citra Dengan Menggunakan Web Cam Pada Kendaraan Bergerak Di Jalan Raya,” JIPI (Jurnal Ilm. Penelit. dan Pembelajaran Inform., vol. 1, no. 01, pp. 1–6, 2016, doi: 10.29100/jipi.v1i01.18.

B. Sit, M. Iqbal Quraishi, and P. Student, “A Review Paper on Hough Transform and it’s Applications in Image Processing,” Int. J. Innov. Res. Sci. Eng. Technol. (An ISO, vol. 3297, p. 13, 2007, [Online]. Available: www.ijirset.com.

V. Georgieva, P. Petrov, and A. Mihaylova, “GUI for Circular and Elliptic Objects Detection in Digital Images GUI für kreisförmigen und ellipsenförmigen Objektserkennung in den,” vol. 1, pp. 7–10, 2017.

R. M. Putra, R. D. Puriyanto, K. Uad, and J. Ring, “Sistem Deteksi dan Pelacakan Bola dengan Metode Hough circle Transform Menggunakan Kamera Omnidirectional pada Robot Sepak Bola Beroda,” vol. 3, no. 3, pp. 176–184, 2021, doi: 10.12928/biste.v3i3.4786.

R. A. Rizal, I. S. Girsang, and S. A. Prasetiyo, “Klasifikasi Wajah Menggunakan Support Vector Machine (SVM),” REMIK (Riset dan E-Jurnal Manaj. Inform. Komputer), vol. 3, no. 2, p. 1, 2019, doi: 10.33395/remik.v3i2.10080.

H. M and S. M.N, “A Review on Evaluation Metrics for Data Classification Evaluations,” Int. J. Data Min. Knowl. Manag. Process, vol. 5, no. 2, pp. 01–11, 2015, doi: 10.5121/ijdkp.2015.5201.




DOI: https://doi.org/10.33365/jti.v16i2.1952

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