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: Mon, 13-Apr-2015

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