dc.contributor.advisor |
Klette, R |
en |
dc.contributor.advisor |
Nicolescu, R |
en |
dc.contributor.author |
Geng, Haokun |
en |
dc.date.accessioned |
2011-02-27T23:24:26Z |
en |
dc.date.issued |
2011 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/6500 |
en |
dc.description |
Full text is available to authenticated members of The University of Auckland only. |
en |
dc.description.abstract |
In environmental surveillance, it is always important to find out the presence of the selected small animals when ecologists decide to study rare species or detect threatened species. Ecology experts use tracking tunnels and inked tracking cards as a standard procedure to collect tracks of the target species. Analysing tracks or footprints can provide relevant information of what kind of species they might be, and the density of this identified species. Unfortunately, distinguishing them among many morphologically similar species through analysing their footprints is extremely difficult, and even very experienced experts find it hard to provide reliable results on footprints identification, this task also requires great amount of efforts on observation. In recent years, multimedia imaging technology has become a good example for applying computer science technologies to many other study areas or industries, in order to improve accuracy, productivity, and reliability. The focus of this research is on applying the multimedia imaging processing technologies to the study field of environmental surveillance, and finally to provide an integrated solution for track recognition of species. To achieve these initial objectives, this thesis introduces an automatic track recognition algorithm for rat footprints based on imaging processing technology. Moreover, it also presents a design of an on-line database with a proper web application, for ecologists to store, to share and to analyse scanned footprints of small species. As more image data is gathered, this database will become valuable for related academic researches in this area. |
en |
dc.publisher |
ResearchSpace@Auckland |
en |
dc.relation.ispartof |
Masters Thesis - University of Auckland |
en |
dc.relation.isreferencedby |
UoA99215498214002091 |
en |
dc.rights |
Restricted Item. Available to authenticated members of The University of Auckland. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.title |
Track Recognition for Environmental Surveillance |
en |
dc.type |
Thesis |
en |
thesis.degree.discipline |
Computer Science |
en |
thesis.degree.grantor |
The University of Auckland |
en |
thesis.degree.level |
Masters |
en |
dc.rights.holder |
Copyright: the author |
en |
pubs.elements-id |
206627 |
en |
pubs.record-created-at-source-date |
2011-02-28 |
en |
dc.identifier.wikidata |
Q112158768 |
|