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
Autonomous Validation through Visual Inspection
Halmstad University, School of Information Technology.
Halmstad University, School of Information Technology.
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The industrial testing phase of graphical user interfaces and the behaviour of screens, is still involving manual tests with human interaction. This type of testing is particularly difficult and time consuming to manually perform, due to time sensitive messages and information used within these interfaces. This thesis address this issue by introducing an approach to automate this process by utilizing high grade machine vision cameras and existing algorithm implementations from OpenCV 3.2.0. By knowing the expected graphical representation in advance, a comparison between the actual outcome and this expectation can be evaluated by applying image processing algorithms. It is found that this approach presents an Equal Error Rate of 6% while still maintaining a satisfactory time performance, in relation to the timeframe requirement of these time sensitive messages. Accuracy and time performance is profoundly affected by hardware equipment, partially due to the immense amount of image processing involved.

Place, publisher, year, edition, pages
2017. , 50 p.
Keyword [en]
computer vision, opencv, machine vision, testing, test, gui
National Category
Robotics
Identifiers
URN: urn:nbn:se:hh:diva-34366OAI: oai:DiVA.org:hh-34366DiVA: diva2:1116077
External cooperation
Diadrom Systems AB
Supervisors
Examiners
Available from: 2017-06-29 Created: 2017-06-27 Last updated: 2017-07-12Bibliographically approved

Open Access in DiVA

fulltext(2694 kB)25 downloads
File information
File name FULLTEXT02.pdfFile size 2694 kBChecksum SHA-512
7d02f1c591c09f6e41a0b18324ac8fbb489efbe41de8ecafd624bd5290d37af3b05cdac8199ca0de7ae65226ee468d1dcbe6415525980d9c69ab5fe05f42c3e5
Type fulltextMimetype application/pdf

By organisation
School of Information Technology
Robotics

Search outside of DiVA

GoogleGoogle Scholar
Total: 25 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 123 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