Vehicle Classification using Haar Cascade Classifier Method in Traffic Surveillance System
| Main Authors: | Ramadhani, Moch Ilham, Minarno, Agus Eko, Cahyono, Eko Budi |
|---|---|
| Format: | Article PeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
Program Studi Elektro dan Informatika Fakultas Teknik Universitas Muhammadiyah Malang
, 2018
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| Subjects: | |
| Online Access: |
http://eprints.umm.ac.id/60746/18/Peer%20Review%20-%20Minarno%20-%20Haar-like%20Feature%20AdaBoost%20Cascade%20Classifier%20Vehicle%20Detection%20Digital%20Image%20Processing.pdf http://eprints.umm.ac.id/60746/19/Similarity%20-%20Ramadhani%20Minarno%20Cahyono%20-%20Haar-like%20Feature%20AdaBoost%20Cascade%20Classifier%20Vehicle%20Detection%20Digital%20Image%20Processing.pdf http://eprints.umm.ac.id/60746/20/Ramadhani%20Minarno%20Cahyono%20-%20Haar-like%20Feature%20AdaBoost%20Cascade%20Classifier%20Vehicle%20Detection%20Digital%20Image%20Processing.pdf http://eprints.umm.ac.id/60746/ https://kinetik.umm.ac.id/index.php/kinetik/article/view/546 |
Daftar Isi:
- Object detection based on digital image processing on vehicles is very important for establishing monitoring system or as alternative method to collect statistic data to make efficient traffic engineering decision. A 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 was used to present visual shape of vehicle, and AdaBoost machine learning algorithm was also employed to make a strong classifier by combining specific classifier into a cascade filter to quickly remove background regions of an image. At the testing section, the output was tested over 8 realistic video data and achieved high accuracy. The result was set 1 as the biggest value for recall and precision, 0.986 as the average value for recall and 0.978 as the average value for precision.