Deteksi Kecepatan Kendaraan Berjalan di Jalan Menggunakan OpenCV

Andrew Andrew, Joko Lianto Buliali, Arya Yudhi Wijaya
Submission Date: 2017-07-20 14:34:03
Accepted Date: 2018-01-09 21:27:31


Saat ini, di berbagai kota telah dipasang CCTV pada setiap ruas jalan. Dari CCTV, dapat diketahui kondisi lalu lintas, namun tidak dapat diketahui kecepatan setiap kendaraaan. Oleh karena itu, dibuat perangkat lunak yang dapat mendeteksi kecepatan kendaraan di ruas jalan dari video yang diambil oleh CCTV. Tujuan lainnya adalah untuk mengetahui perbedaan hasil deteksi kecepatan dengan berbagai nilai FPS (Frame Per Second).

Input untuk aplikasi ini adalah video (.avi). Pertama, sistem mengambil Region of Interest (ROI). Selanjutnya, sistem melakukan background subtraction, membuat garis awal dan akhir, memperbarui posisi kendaraan, dan menyimpan hasil kecepatan rata-rata kendaraan ke berkas Excel (.xls).

Skenario uji coba dilakukan berdasarkan nilai FPS pada video (30 FPS, 27 FPS, 25 FPS, dan 20 FPS). Setiap skenario terdapat sub-skenario berdasarkan posisi koordinat garis akhir {(296,0); (282,0); (270,0); dan (248,0)}. Pengujian dilakukan 5 kali setiap skenario, lalu dibandingkan dengan hasil sebenarnya untuk mendapatkan nilai error pada sistem. Error terkecil yang dihasilkan sistem sebesar 2,75% dengan posisi koordinat garis akhir di (282,0) pada skenario 30 FPS.


CCTV; OpenCV; ROI; FPS; Deteksi Kecepatan


A. G. Rad, A. Dehghani, and M. R. Karim, “Vehicle speed detection in video image sequences using CVS method,” Int. J. Phys. Sci., vol. 5, no. 17, pp. 2555–2563, 2010.

H. S. Sundoro and A. Harjoko, “VEHICLE COUNTING AND VEHICLE SPEED MEASUREMENT BASED ON VIDEO PROCESSING,” J. Theor. Appl. Inf. Technol., vol. 84, no. 2, p. 233, 2016.

“OpenCV,” Wikipedia. 29-Apr-2017.

“OpenCV library.” [Online]. Available: [Accessed: 07-May-2017].

“OpenCL,” Wikipedia. 25-Apr-2017.

“Frame rate,” Wikipedia. 29-Apr-2017.

“Background subtraction,” Wikipedia. 08-Feb-2017.

“OpenCV: Background Subtraction.” [Online]. Available: [Accessed: 07-May-2017].

Z. Zivkovic, “Improved adaptive Gaussian mixture model for background subtraction,” in Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on, 2004, vol. 2, pp. 28–31.

Z. Zivkovic and F. van der Heijden, “Efficient adaptive density estimation per image pixel for the task of background subtraction,” Pattern Recognit. Lett., vol. 27, no. 7, pp. 773–780, May 2006.

“e (mathematical constant),” Wikipedia. 06-May-2017.

“Region of interest,” Wikipedia. 12-Jan-2017.

S. Suzuki and Abe, Keiichi, “Topological structural analysis of digitized binary images by border following,” Comput. Vis. Graph. Image Process., vol. 30, no. 1, pp. 32–46, 1985.

C. Chia Yik, “Vehicle Tracking and Speed Estimation System,” University Malaysia Pahang, Malaysia, Jun. 2012.

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