Real-time segmentation for baggage tracking on a cost effective embedded platform
by Andrew Gilman; Martin Johnson
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 13, No. 4, 2014

Abstract: This paper describes segmentation and tracking parts of a machine vision based airport baggage tracking system. A simplified codebook based background subtraction method is used to segment the bag from a semi-static background. Morphological processing using an integral image is used to filter the foreground mask and the bag location is found using statistical methods. The system was implemented on a cost effective embedded processor and runs in real time at 30 fps. Five ARM based embedded platforms are evaluated and it is shown that all of them are capable of the required performance.

Online publication date: Tue, 14-Apr-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Systems Technologies and Applications (IJISTA):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com