159
Views
1
CrossRef citations to date
0
Altmetric
Articles

Logistics vehicle tracking method based on intelligent vision

Pages 276-282 | Received 30 Aug 2017, Accepted 22 Oct 2017, Published online: 10 Nov 2017
 

ABSTRACT

The traditional logistics vehicle tracking method lacks the function of active identification and switch tracking. Therefore, in the presence of interference, there are some problems such as interference, hard recognition, handoff delay and tracking loss for the tracking of no difference vehicle. Therefore, a logistics vehicle tracking method based on intelligent vision is proposed. Firstly, the visual vehicle is segmented by visual vehicle, and then image feature of logistics vehicle is obtained, the visual intelligent tracking method based on region matching and Kalman filter is used to change the logistics vehicle without difference. In the handover process, the Kalman filter is used to predict the position of the vehicle, and the compensation switching delay is compensated. According to consistency of the vehicle running state and the corresponding lane, no-difference switching logistics vehicle tracking is realized. The experimental results show that the algorithm is not demanded for the initial background. The algorithm can automatically generate the current frame background regardless of the presence of the moving vehicle in the initial background. The logistics efficiency of the method is higher than 90%; error tracking rate is less than 1%.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 288.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.