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Proceedings Paper

Vector analysis for direction prediction on image strings
Author(s): Andrew J. Tickle; Josef E. Grindley
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Paper Abstract

Vector analysis is a well-developed field that deals with details about line, surface and volume integrals which can be solved analytically to provide solutions to many problems. Using vector analysis, a curve can be divided up into many small arcs, each of which is a position vector. The summation of these position vectors can be used to represent the curve in detail; this is known as the total vector field. In this paper, there is shown a vector analysis methodology when applied to the wake immediately after a moving or stationary object, caused by the movement of the object through free space or the surrounding medium moving around the object respectively. The aim was to create a system that can determine the vectors between successive images in a video with the end result being able to establish an overall trajectory of the object. This could be implemented on a Field Programmable Gate Array (FPGA) or other device to be deployed in the field to track any type of object. If the device’s orientation with magnetic north-south is known, the direction of the object is travelling in can be calculated and then relayed on. This could be useful as an easily deployable warning system for the armed forces or rescue services to inform personnel of potential incoming threats. This work builds upon the Morphological Scene Change Detection (MSCD) mechanism implemented in the DSP Builder environment and describes how the changes allow the system to track the wake and plot its trajectory. System simulations of real world data are shown and the resultant imagery is then discussed. Furthermore, tests are conducted on single objects and then multiple objects to investigate how the system responds as real world situations are likely to have more than a single object.

Paper Details

Date Published: 19 October 2012
PDF: 8 pages
Proc. SPIE 8540, Unmanned/Unattended Sensors and Sensor Networks IX, 85400K (19 October 2012); doi: 10.1117/12.974764
Show Author Affiliations
Andrew J. Tickle, Coventry Univ. (United Kingdom)
Josef E. Grindley, Coventry Univ. (United Kingdom)

Published in SPIE Proceedings Vol. 8540:
Unmanned/Unattended Sensors and Sensor Networks IX
Edward M. Carapezza; Henry J. White, Editor(s)

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