A novel video detection design based on modified adaboost algorithm and HSV model

Xiao Luo, Huatao Zhao, Harutoshi Ogai, Chen Zhu

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In modern traffic systems, accurate video detection is a key challenge for traffic management. Aiming at the problem of public bus detection, this paper proposes a video detection method to well recognize the buses. Firstly, we employ the foreground detection method to find the moving vehicles. And then a training classifier which consists of the improved Adaboost algorithm and Haar-like features is proposed to filter undesired vehicles. Secondly, we use the Canny operator to locate bus characteristics, and further detect the bus with the modified HSV model. This design is tested on the Visual Stadio and OpenCV platform in which load the urban transport data as the samples. The test results show that our detection method has better robustness than both three-frame differential method and hybrid Gaussian method, and the accuracy of detection on the window positioning is more than 93 percent.

本文言語English
ホスト出版物のタイトルProceedings of 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2328-2331
ページ数4
ISBN(電子版)9781467389778
DOI
出版ステータスPublished - 2017 9 29
イベント2nd IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2017 - Chongqing, China
継続期間: 2017 3 252017 3 26

Other

Other2nd IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2017
CountryChina
CityChongqing
Period17/3/2517/3/26

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Information Systems
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Information Systems and Management

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