Helmet Detection Based on Cascade Classifier and Adaptive Boosting

Authors

DOI:

https://doi.org/10.33633/jais.v8i2.7392

Abstract

The increasing number of traffic accidents caused by motorcyclists not wearing helmets has led to an increase in the number of studies related to road safety surveillance. The research system used is an automatic system to detect whether the motorcyclist is wearing a helmet or not. Many studies use image processing systems, deep learning and computer vision. In this research, Cascade Classifier and Adaptive Boosting have been implemented for the process of identifying motorcycle riders with helmets and without helmets. The number of datasets used is 500 datasets with labels on the image of the driver with a helmet and the image of the driver without a helmet. Based on the test results, an accuracy of 90% has been obtained

Author Biographies

Ajib Susanto, universitas dian nuswantoro semarang

Dosen Teknik informatika S1Fakultas ilmu komputeruniversitas Dian Nuswantoro Semarang

Yupie Kusumawati, Dian Nuswantoro University

Department of Information System

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Published

2023-07-31

Issue

Vol. 8 No. 2 (2023): Journal of Applied Intelligent System

Section

Articles

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