Thesis (MScEng (Mathematical Sciences)--University of Stellenbosch, 2009. / ENGLISH ABSTRACT: To reliably classify parts of an image sequence as foreground or background
is an important part of many computer vision systems, such as video surveillance,
tracking and robotics. It can also be important in applications where
bandwidth is the limiting factor, such as video conferencing.
Independent foreground motion is an attractive source of information for this
task, and with static cameras, background subtraction is a particularly popular
type of approach. The idea behind background subtraction is to compare
the current image with a reference image of the background, and from there
decide on a pixel by pixel basis, what is foreground and what is background
by observing the changes in the pixel sequence.
The problem is to get the useful reference image, especially when large parts
of the background are occluded by moving/stationary foreground objects; i.e.
some parts of the background are never seen.
In this thesis four algorithms are reviewed that segment an image sequence
into foreground and background components with varying degrees of success
that can be measured on speed, comparative accuracy and/or memory requirements.
These measures can be then effectively used to decide the application
scope of the individual algorithms. / AFRIKAANSE OPSOMMING: Om betroubaar dele van ’n beeld reeks te klassifiseer as voorgrond of agtergrond
is ’n belangrike deel van baie rekenaarvisie sisteme, byvoorbeeld video
bewaking, volging en robotika. Dit kan ook belangrik wees in toepassings waar
bandwydte die beperkende faktor is, byvoorbeeld video konferensie gesprekke.
Onafhanklik voorgrond beweging is ’n aantreklike bron van informasie vir hierdie
taak, en met statiese kameras, is agtergrond aftrekking ’n populêre benadering.
Die idee agter agtergrond aftrekking is om die huidige beeld met
’n naslaan beeld van die agtergrond te vergelyk, en daarvandaan besluit op ’n
piksel-na-piksel basis, wat is voorgrond en wat is agtergrond deur die observasies
van die veranderinge in die piksel-reeks.
Die probleem is om die naslaan beeld te kry om mee te werk, veral wanneer
groot dele van die agtergrond onsigbaar bly as gevolg van bewegende of stilstaande
voorgrond objekte en sommige dele van die agtergrond word dalk nooit
gesien nie.
In hierdie tesis word vier algorithms ondersoek wat ’n beeld reeks segmenteer
in respektiewe voorgrond en agtergrond komponente met wisselende grade van
sukses wat gemeet kan word deur spoed, vergelykbare akkuraatheid en/of geheu gebruik. Hierdie metings kan dan effektief gebruik word om die applikasie
veld van die individuele algoritmes the bepaal.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/2303 |
| Date | 12 1900 |
| Creators | Profitt, Barton |
| Contributors | Hunter, K. M., Herbst, B. M, University of Stellenbosch. Faculty of Science. Dept. of Mathematical Sciences. |
| Publisher | Stellenbosch : University of Stellenbosch |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Rights | University of Stellenbosch |
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