Speed Bump System Based on Vehicle Speed Using Adaptive Background Subtraction with Haar Cascade Classifier

Muhammad Zulfikri, Wirajaya Kusuma, Sirojul Hadi, Husain Husain, Rifqi Hammad, Lalu Zazuli Azhar Mardedi

Abstract


Driving at high speed and recklessly is the main cause of traffic accidents. In several places speed bumps are installed as a medium to warn drivers to slow down the speed of the vehicle, but the installation of speed bumps in several places has become a problem in itself with inconvenience for drivers traveling at low speeds, so it is necessary to develop an intelligent system to warn drivers when speeding. vehicles break safety boundaries, making drivers safer and more comfortable. At the vehicle identification stage, a combination of the Adaptive Background Subtraction method with the Haar Cascade Classifier is proposed, and vehicle speed estimation is carried out by calculating the time difference in the detection area or Region of Interest (ROI). Testing was carried out using traffic videos with three conditions, namely day, evening and night, with each condition using the same object data, namely 55 images of car objects. The proposed method produces car detection accuracy with an average of 85% and MSE 0.5 in vehicle speed measurements

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References


P. Viola and M. Jones, “Rapid Object Detection using A Boosted Cascade of Simple Features,” IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. , vol. 1, pp. 511–518, 2001, doi: 10.1109/CVPR.2001.990517.

P. Viola and MJ Jones, “Robust Real-Time Face Detection,” Int. J. Comput. Vis. , vol. 57, no. 2, pp. 137–154, May 2004, doi: 10.1023/B:VISI.0000013087.49260.fb.

RPMD Labib, S. Hadi, and PD Widayaka, "Low Cost System for Face Mask Detection based Haar Cascade Classifier Method," MATRIK J. Management, Tech. Inform. and Computer Engineering. , vol. 21, no. 1, pp. 21–30, 2021, doi: 10.30812/matrik.v21i1.1187.

B. Santoso and R.P Kristianto, "Implementation of using Opencv in Face Recognition for Student Lecture Attendance Systems," Sistemasi, vol. 9, no. 2, p. 352, 2020, doi: 10.32520/stmsi.v9i2.822.

M. Zulfikri, E. Yudaningtyas, K. Vehicle, H. Cascade, and J. Teknologi, "Speed Bump Enforcement System based on Vehicle Speed Classified by the Haar Cascade Classifier," J. Teknol. and Sis. Inf. , vol. 7, no. 1, pp. 12–18, 2019, doi: 10.14710/jtsiskom.7.1.2019.12-18.

H.T. Wibowo, E. P. Wibowo, and R.K. Harahap, "Implementation of Background Subtraction for Counting Vehicles using Mixture of Gaussians with ROI Optimization," in 2021 Sixth International Conference on Informatics and Computing (ICIC) , 2021, pp. 1–6. doi: 10.1109/ICIC54025.2021.9632950.

K. Adi, A. P. Widodo, C. E. Widodo, A. Pamungkas, and A. B. Putranto, “Automatic Vehicle Counting using Background Subtraction Method on Gray Scale Images and Morphology Operation,” J. Phys. Conf. Ser., vol. 1025, no. 1, 2018, doi: 10.1088/1742-6596/1025/1/012025.

P. K. Thadagoppula and V. Upadhyaya, “Speed Detection using Image Processing,” in Proceeding - 2016 International Conference on Computer, Control, Informatics and its Applications: Recent Progress in Computer, Control, and Informatics for Data Science, IC3INA 2016, 2017, pp. 11–16. doi: 10.1109/IC3INA.2016.7863015.

NA Mandellos, I. Keramitsoglou, and CT Kiranoudis, “A Background Subtraction Algorithm for Detecting and Tracking Vehicles,” Expert Syst. Appl. , vol. 38, no. 3, pp. 1619–1631, 2011, doi: 10.1016/j.eswa.2010.07.083.

D. Alamsyah, "Car Recognition in Digital Images using HOG-SVM," JATISI (Journal of Information Technology and Information Systems) , vol. 1, no. 2, pp. 162–168, 2017.

PC Useche Murillo, RJ Moreno, and JO Pinzon Arenas, “Comparison between CNN and Haar Classifiers for Surgical Instrumentation Classification,” Contemp. Eng. Sci. , vol. 10, no. 28, pp. 1351–1363, 2017, doi: 10.12988/ces.2017.711157.

R. Andrie Asmara, M. Ridwan, and G. Budiprasetyo, “Haar Cascade and Convolutional Neural Network Face Detection in Client-Side for Cloud Computing Face Recognition,” in 2021 International Conference on Electrical and Information Technology (IEIT), 2021, pp. 1–5. doi: 10.1109/IEIT53149.2021.9587388.

F. A. Mahaputra, I. U. V. Simanjuntak, Yuliza, Heryanto, A. D. Rochendi, and L. M. Silalahi, “Comparative Study Of Convolutional Neural Network And Haar Cascade Performance On Mask Detection Systems using Matlab,” in 2022 9th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), 2022, pp. 74–78. doi: 10.23919/EECSI56542.2022.9946467.

J. Wu, Z. Liu, J. Li, C. Gu, M. Si, and F. Tan, “An Algorithm for Automatic Vehicle Speed Detection using Video Camera,” in 2009 4th International Conference on Computer Science & Education, 2009, pp. 193–196. doi: 10.1109/ICCSE.2009.5228496.

C. Y. Ho, H. Y. Lin, and L. T. Wu, “Intelligent Speed Bump System with Dynamic License Plate Recognition,” Proc. IEEE Int. Conf. Ind. Technol., vol. 5, no. 1, pp. 1669–1674, 2016, doi: 10.1109/ICIT.2016.7475013.

L. E. Y. Mimbela, “A Summary of Vehicle Detection and Surveillance Technologies used in Intelligent Transportation Systems,” Fed. Highw. Adm. Intell. Transp. Syst. Progr. Off., 2007.

KMR Indonesia, "Decree of the Minister of Transportation no. 3 of 1994 Concerning Road User Control and Safety Equipment." Jakarta, 1994.




DOI: https://doi.org/10.32520/stmsi.v13i3.3921

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