Haar-like feature based real-time neuro car detection system

Naba, Agus; Pratama, Boby Mugi; Nadhir, Ahmad; Harsono, Heru

doi:10.1109/issimm.2016.7803724

Cited by 3 publications

(1 citation statement)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Metode HLF juga pernah digunakan untuk mendeteksi makhluk hidup yang bergerak (Uddin et al, 2015). Metode ini belum pernah digunakan untuk mendeteksi objek yang bergerak dan mengapung, akan tetapi sudah pernah teruji pada benda bergerak lainnya di darat seperti kendaraan bermotor (Moghimi et al, 2018;Hiromoto et al, 2007;Al Jarouf et al, 2018;Naba et al, 2017;Bencheriet 2018).…”

Section: Metode Haar Like Feature (Hlf)unclassified

Deteksi Objek Terapung pada Sungai Martapura dengan Metode Haar Like Feature Menggunakan Kamera Smart Phone

Saubari¹,

Ansari²,

Gazali³

2019

J. Sistem Info. Bisnis

View full text Add to dashboard Cite

Martapura river is the center of Banjarmasin’s local life, especially for water transportation and its famous floating market tourism spot. Due to various floating objects in Martapura river, a method to detect those objects is needed to control the condition of the river. In general, there are several methods to detect objects such as Gaussian, Support Vector Machine (SVM), Independent Component Analysis (ICA) and the newest method called Haar Like Feature (HLF). Those first three methods often used to detect moving object, while HLF mostly used to detect human’s face. This research aimed to examine the use of HLF method to detect floating objects in Martapura river by using smartphone’s camera with the specification of 16Megapixel and 1080p resolution. The data collected with random sampling technique in two different spots in Banjarmasin at different times. Images and videos then examined using HLF method. The result shows that HLF method by using smartphone camera cannot be used to identify any floating objec

show abstract

Section: Metode Haar Like Feature (Hlf)unclassified

Deteksi Objek Terapung pada Sungai Martapura dengan Metode Haar Like Feature Menggunakan Kamera Smart Phone

Saubari¹,

Ansari²,

Gazali³

2019

J. Sistem Info. Bisnis

View full text Add to dashboard Cite

show abstract

Designing a neural network for vehicle type classification using extended Haar features

Pratama

Supriyadi

Gultom

2018

2018 2nd Borneo International Conference on Applied Mathematics and Engineering (BICAME)

View full text Add to dashboard Cite

Enhancing Front-Vehicle Detection in Large Vehicle Fleet Management

Kung²,

Chen

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

Transportation safety has been widely discussed for avoiding forward collisions. The broad concept of remote sensing can be applied to detect the front of vehicles without contact. The traditional Haar features use adjacent rectangular areas for many ordinary vehicle studies to detect the front vehicle images in practice. This paper focused on large vehicles using a front-installed digital video recorder (DVR) with a near-infrared (NIR) camera. The views of large and ordinary vehicles are different; thus, this study used a deep learning method to process progressive improvement in moving vehicle detection. This study proposed a You Only Look Once version 4 (YOLOv4) supplemented with the fence method, called YOLOv4(III), to enhance vehicle detection. This method had high detection accuracy and low false omission rates using the general DVR equipment, and it provided comparison results. There was no need to have a high specification front camera, and the proposed YOLOv4(III) was found to have competitive performance. YOLOv4(III) reduced false detection rates and had a more stable frame per second (FPS) performance than with Haar features. This improved detection method can give an alert for large vehicle drivers to avoid serious collisions, leading to a reduction in the waste of social resources.

show abstract

Haar-like feature based real-time neuro car detection system

Cited by 3 publications

References 6 publications

Deteksi Objek Terapung pada Sungai Martapura dengan Metode Haar Like Feature Menggunakan Kamera Smart Phone

Deteksi Objek Terapung pada Sungai Martapura dengan Metode Haar Like Feature Menggunakan Kamera Smart Phone

Designing a neural network for vehicle type classification using extended Haar features

Enhancing Front-Vehicle Detection in Large Vehicle Fleet Management

Contact Info

Product

Resources

About