uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • 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
Evaluation and Improvement of Image Acquisition and Processing Methods for the BioNanoLab
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
2009 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

BioNanoLab is a project aimed towards developing a prototype for a system capableof fast and sensitive detection of biological warfare agents. One of the important partsin the project is image acquisition and processing. My task was to evaluate andimprove these methods. The first step was to choose a machine vision library to useand then to write a program for acquiring images from line scan cameras to disctrough frame grabbers and to write code for processing the images.

The two different machine vision libraries I tested were Sapera Essential andCommon vision blox (CVB). Sapera Essential is a machine vision library from Dalsa. Itis platform dependent as it only works for Dalsa hardware. CVB on the other hand isa hardware independent machine vision library from Stemmer imaging.

The run times for the two libraries were almost the same but Sapera Essential waschosen as the winner because we wanted the more low level control which Saperaoffers, as it is written specifically for the hardware we used. Another reason was thatthe blob counting for CVB started to miscount some times.

Place, publisher, year, edition, pages
2009.
Series
IT ; 09 021
Identifiers
URN: urn:nbn:se:uu:diva-108018OAI: oai:DiVA.org:uu-108018DiVA, id: diva2:233905
Presentation
(English)
Uppsok
Technology
Supervisors
Examiners
Available from: 2009-09-03 Created: 2009-09-03 Last updated: 2009-11-18Bibliographically approved

Open Access in DiVA

fulltext(984 kB)543 downloads
File information
File name FULLTEXT01.pdfFile size 984 kBChecksum SHA-512
92381a9542ae1e2fe5b84bd1d6f796b16fa0d23f91b1603668d9eebd955800dd2d4b35dcfb224e51827eae636e7a4d67e7f74836721037c7a0c64b041a71d2f5
Type fulltextMimetype application/pdf

By organisation
Department of Information Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 543 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

urn-nbn

Altmetric score

urn-nbn
Total: 660 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • 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