hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Crack detection
Halmstad University, School of Business and Engineering (SET).
Halmstad University, School of Business and Engineering (SET).
1995 (English)Independent thesis Advanced level (degree of Master (One Year))Student thesis
Abstract [en]
Computer vision is used today in a wide spectrum of industrial applications from guiding robots to inspection of machine parts. In general computer vision is used for high speed, unqualified tasks or in hostile environments and on high quality images (with high contrast and high Signal to Noise Ratio). This master thesis presents work on crack detection in noisy images whit low contrast. We present different methods for detecting cracks on rough surfaces. The methods we used are mathematical morphology and in particular gray scale morphology and neural networks.
Place, publisher, year, edition, pages
1995.
Keywords [en]
image analysis, articial neural network, crack detection
Identifiers
URN: urn:nbn:se:hh:diva-7201Local ID: U1070OAI: oai:DiVA.org:hh-7201DiVA, id: diva2:362250
Uppsok
Technology
Note
Denna uppsats kan beställas från arkivet / This paper can be ordered from the archive. Kontakta / Contact: arkivet@hh.seAvailable from: 2010-11-09 Created: 2010-11-09Bibliographically approved

Open Access in DiVA

No full text in DiVA

By organisation
School of Business and Engineering (SET)

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 29 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf