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Article | 27-January-2020

Research on Improved Adaptive ViBe Algorithm For Vehicle Detection

I. INTRODUCTION Vehicle detection is the key step of video vehicle recognition, which aims to obtain the location of vehicle for further recognition. For each pixel, its background can usually be built using a model. At present, there are three methods for moving object detection: optical flow method[1], frame difference method[2], background subtraction method[3]. Based on the motion vector of pixels, the optical flow method can detect and track the target, but it has a large amount of

Kun Jiang, Jianguo Wang

International Journal of Advanced Network, Monitoring and Controls, Volume 4 , ISSUE 4, 11–17

Research Article | 01-September-2014


Abstract- In intelligent transportation system, research on vehicle detection and classification has high theory significance and application value. According to the traditional methods of vehicle detection which can’t be well applied in challenging scenario, this paper proposes a novel Bayesian fusion algorithm based on Gaussian mixture model. We extract the features of vehicle from images, including shape features, texture features, and the gradient direction histogram features after

Yiling Chen, GuoFeng Qin

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 3, 1077–1094

Article | 01-June-2016


the proposed system are image preprocessing, image segmentation, and vehicle detection and counting the number of vehicles. Images are captured from the traffic monitoring cameras installed in highways. Results from testing phase using thirty images with varying brightness, contrast, and quality taken from different cameras during daylight showed that the accuracy of the system in counting the number of vehicles is 78.21%.

Chastine Fatichah, Joko Lianto Buliali, Ahmad Saikhu, Silvester Tena

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 765–779

Article | 07-May-2018

Research on Vehicle Detection Method Based on Background Modeling

Zhichao Lian, Zhongsheng Wang

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 2, 6–9

Article | 16-December-2013

Virtual Detection Zone in smart phone, with CCTV, and Twitter as part of an Integrated ITS

B. Hardjono, A. Wibisono, A. Nurhadiyatna, I. Sina, W. Jatmiko

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 5, 1830–1868

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