Vehicle Classification using Haar Cascade Classifier Method in Traffic Surveillance System

Vehicle Classification using Haar Cascade Classifier Method in Traffic Surveillance System

Moch Ilham Ramadhani, Agus Eko Minarno, Eko Budi Cahyono

Abstract

Object Vehicle detection based on digital image processing is very important for making monitoring system or as alternative method to collect statistic data to make efficient traffic engineering decision. Vehicle counter program based on traffic video feed for specific type of vehicle using Haar Cascade Classifier was made as the output of this research. Firstly, Haar-like feature used to presented visual shape of vehicle, and AdaBoost machine learning algorithm used to make a strong classifier with combining specific classifier into cascade filter to quickly remove background regions of image. At testing section, the output was tested over 8 realistic video data and achieved high accuracy. The result was set 1 as a biggest value for recall and precision, 0.986 as average value for recall and 0.978 as average value for precision.

Keywords

Haar-like feature, AdaBoost, Cascade classifier, Vehicle Detection, Digital Image Processing

References

Kementerian Perhubungan, Statistik Perhubungan volume l. 2016.

Badan Pusat Statistik Provinsi DKI Jakarta, Statistik Transportasi DKI Jakarta 2015. 2015.

N. Redhantika, “Kepadatan lalu lintas di kota malang,” Univ. Merdeka Malang, pp. 1–10, 2014.

R. Anwar, “Menentukan Nilai Satuan Mobil Penumpang Kendaraan Di Kotamadya Banjarmasin,” vol. 1, no. 1, pp. 22–27, 2000.

Fajar Mit Cahyana, “Perancangan Program Penghitung Jumlah Kendaraan Satu Arah Menggunakan Bahasa Pemograman C++ dengan Pustaka OpenCV,” Univ. Brawijaya, 2014.

A. Helmi, “Apikasi Deteksi Tingkat Kepadatan Lalu Lintas Berdasarkan Jumlah Kendaraan Yang Lewat Menggunakan OpenCV,” 2015.

C.-J. Lee, “obstacle detetction and avoidance via cascade classifier for wheeled mobile robot,” Int. Conf. Mach. Learn. Cybern., p. 5, 2015.

M. Syarif, P. Studi, T. Informatika, F. I. Komputer, U. Dian, and N. Semarang, “Deteksi Kedipan Mata Dengan Haar Cascade Classifier Dan Contour Untuk Password Login,” Techno.com, vol. 14, no. 4, pp. 242–249, 2015.

P. Viola and M. M. J. Jones, “Robust Real-Time Face Detection,” Int. J. Comput. Vis., vol. 57, no. 2, pp. 137–154, 2004.

A. Mordvintsev, “OpenCV-Python Tutorials Documentation Release beta,” 2017.

J. Howse, OpenCV Computer Vision with Python. 2013.

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