DOI: https://doi.org/10.14710/jtsiskom.7.1.2019.12-18

Sistem Penegakan Speed Bump Berdasarkan Kecepatan Kendaraan yang Diklasifikasikan Haar Cascade Classifier

Speed Bump Enforcement System Based on Vehicle Speed Classified by Haar Cascade Classifier

Department of Electrical Engineering, Universitas Brawijaya, Indonesia

Received: 3 Dec 2018; Revised: 29 Jan 2019; Accepted: 30 Jan 2019; Available online: 31 Mar 2019; Published: 31 Jan 2019.
Open Access Copyright (c) 2019 Jurnal Teknologi dan Sistem Komputer
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Abstract
Driving at high speed is among the frequent causes of accidents. In this research, a warning system was developed to warn drivers when their speed beyond the safety limit. Haar cascade classifier was proposed for the detection system which comprises Haar features, integral image, AdaBoost learning, and cascade classifier. The system was implemented using Python OpenCV library and evaluated on road traffic video collected in one way traffic. As a result, the proposed method yields 97.92% of car detection accuracy in daylight and MSE of 2.88 in speed measurement.
Fulltext View|Download Email colleagues
Keywords: speed bump; haar cascade classifier; detection; vehicle speed
Funding: Department of Electrical Engineering, Universitas Brawijaya

Article Metrics:

Article Info
Section: Original Research Articles
Language : ID
Most viewed articles
Pengembangan Sistem Pakar Untuk Diagnosis Penyakit Hepatitis Berbasis Web Menggunakan Metode Certainty Factor Perancangan Game Math Adventure Sebagai Media Pembelajaran Matematika Berbasis Android Optimization for prediction model of palm oil land suitability using spatial decision tree algorithm K-means-SMOTE for handling class imbalance in the classification of diabetes with C4.5, SVM, and naive Bayes Pembuatan Aplikasi Antar-Jemput Laundry Berbasis Web Service pada Platform Android More articles
Most cited articles
Genetic Algorithm for Optimizing Food Composition for Hypertension Patients SMS Security Improvement using RSA in Complaints Application on Regional Head Election’s Fraud Pengembangan Teknologi Informasi Mobile Learning Universitas Diponegoro Berbasis Android Perancangan dan Pengembangan Permainan “Super Sigi” Menggunakan Stencyl Sebagai Media Pengenalan Menyikat Gigi Sistem Pengukur Suhu dan Kelembaban Ruang Server More cited articles
  1. S. L. Jeng, W. H. Chieng, and H. P. Lu, “Estimating Speed using a Side-Looking Single-Radar Vehicle Detector,” IEEE Transactions on Intelligent Transportation Systems, vol. 15, no. 2, pp. 607-614, 2014
  2. C. Y. Ho, H. Y. Lin, and L. T. Wu, “Intelligent Speed Bump System with Dynamic License Plate Recognition,” in 2016 IEEE International Conference on Industrial Technology, Taipei, Taiwan, 14-17 March 2016, pp. 1669–1674
  3. L. E. Y. Mimbela, “A Summary Of Vehicle Detection and Surveillance Technologies Used in Intelligent Transportation Systems,” in International Transport Forum, Leipzig, Germany, May. 2000
  4. D. Bhargava, Kritika; Goyal, “A Video Surveillance System for Speed Detection of Vehicles and Law Enforcement using Automatic Number Plate Recognition,” International Journal of Research in Computer Engineering and Electronics, vol. 3, no. 3, 2014
  5. N. H. Tsani, “Implementasi Deteksi Kecepatan Kendaraan Menggunakan Kamera Webcam dengan Metode Frame Difference,” Skripsi, Universitas Telkom, Bandung, Indonesia, 2017
  6. P. K. Thadagoppula and V. Upadhyaya, “Speed Detection using Image Processing,” in 2016 International Conference on Computer, Control, Informatics and its Applications (IC3INA), Tangerang, Indonesia, Oct. 2016, pp. 11-16
  7. A. Varghese, “Background Subtraction for Vehicle Detection,” in 2015 Global Conference on Communication Technologies (GCCT), Thuckalay, India, Apr. 2015, pp. 380-382
  8. N. A. Mandellos, I. Keramitsoglou, and C. T. Kiranoudis, “A Background Subtraction Algorithm for Detecting and Tracking Vehicles,” Expert Systems with Applications, vol. 38, no. 3, pp. 1619-1631, 2011
  9. Q. Wu, W. Kang, and X. Zhuang, “Real-Time Vehicle Detection with Foreground-Based Cascade Classifier,” IET Image Process., vol. 10, no. 4, pp. 289-296, 2016
  10. P. Viola and M. Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features,” in Proc. 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Kauai, USA, Dec. 2001, pp. I-511-I-518
  11. Andrew, J. L. Buliali, and Y. Wijaya, “Deteksi Kecepatan Kendaraan Berjalan di Jalan Menggunakan OpenCV,” Jurnal Teknik ITS, vol. 6, no. 2, pp. 379–384, 2017
  12. D. K. Ulfa and D. H. Widyantoro, “Implementation of Haar Cascade Classifier for Motorcycle Detection,” in 2017 IEEE International Conference on Cybernetics and Computational Intelligence (CyberneticsCom), Phuket, Thailand, Nov. 2017, pp. 39-44
  13. S. Choudhury, “Vehicle Detection and Counting using Haar Feature-Based Classifier,” in 2017 8th Annual Industrial Automation and Electromechanical Engineering Conference (IEMECON), Bangkok, Thailand, Aug. 2017, pp. 106-109
  14. Keputusan Menteri Perhubungan No 3 Tahun 1994 tentang Alat Pengendali dan Pengaman Pemakai Jalan, Menteri Perhubungan Republik Indonesia, Jakarta, 1994

Last update:

  1. Detection of fake shallots using website-based haar-like features algorithm

    Bambang Agus Setyawan, Mutaqin Akbar. Compiler, 10 (2), 2021. doi: 10.28989/compiler.v10i2.978

  2. Breaches Detection in Zebra Cross Traffic Light Using Haar Cascade Classifier

    Mahada Panji Anggadhita, Yuni Widiastiwi. 2020 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS), 2020. doi: 10.1109/ICIMCIS51567.2020.9354275

Last update: 2024-11-20 22:09:39

  1. Breaches Detection in Zebra Cross Traffic Light Using Haar Cascade Classifier

    Mahada Panji Anggadhita, Yuni Widiastiwi. 2020 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS), 2020. doi: 10.1109/ICIMCIS51567.2020.9354275