📅 28 February 2022
DOI: 10.35671/telematika.v15i1.1222
Detection and Classification of Vehicles on the Bekasi Toll Road Using the Gaussian Mixture Models Method and Morphological Operations
Telematika
Universitas Amikom Purwokerto
📄 Abstract
Traffic surveillance was initially carried out directly using CCTV, but this kind of surveillance was not possible for a full day by the security forces. In addition, with the increasing growth of vehicles in Indonesia, a method is needed that can be used to assist security forces in monitoring traffic such as detecting and automatically counting the number of vehicles. Therefore, in our research, we propose a method that can detect vehicles, and count the number of vehicles from video recordings on the Bintara Bekasi toll road using background substraction methods such as gaussian mixture models and morphological operations. The results showed that the vehicle detection accuracy rate was 86.3636%, the precision was 89.0625%, and the recall was 96.6101%. In this study, vehicle classification was also carried out based on the detection results into two types of vehicles, namely cars and trucks. From the results of the research, the classification accuracy rate was obtained at 85.9649%.
🔖 Keywords
#CCTV; Background Substraction; Gaussian Mixture Models; morphological operations
ℹ️ Informasi Publikasi
Tanggal Publikasi
28 February 2022
Volume / Nomor / Tahun
Volume 15, Nomor 1, Tahun 2022
📝 HOW TO CITE
Kosasih, Rifki; Gunadarma University; Akbar, Hidayat Taufik; Gunadarma University; , "Detection and Classification of Vehicles on the Bekasi Toll Road Using the Gaussian Mixture Models Method and Morphological Operations," Telematika, vol. 15, no. 1, Feb. 2022.
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