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Target-less and targeted multi-camera color calibration
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
2018 (English)Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Multiple camera arrays are beginning to see more widespread use in a variety of different applications, be it for research purposes or for enhancing the view- ing experience in entertainment. However, when using multiple cameras the images produced are often not color consistent due to a variety of different rea- sons such as differences in lighting, chip-level differences e.t.c. To address this there exists a multitude of different color calibration algorithms. This paper ex- amines two different color calibration algorithms one targeted and one target- less. Both methods were implemented in Python using the libraries OpenCV, Matplotlib, and NumPy. Once the algorithms had been implemented, they were evaluated based on two metrics; color range homogeneity and color ac- curacy to target values. The targeted color calibration algorithm was more ef- fective improving the color accuracy to ground truth then the target-less color calibration algorithm, but the target-less algorithm deteriorated the color range homogeneity less than the targeted color calibration algorithm. After both methods where tested, an improvement of the targeted color calibration al- gorithm was attempted. The resulting images were then evaluated based on the same two criteria as before, the modified version of the targeted color cal- ibration algorithm performed better than the original targeted algorithm with respect to color range homogeneity while still maintaining a similar level of performance with respect to color accuracy to ground truth as before. Further- more, when the color range homogeneity of the modified targeted algorithm was compared with the color range homogeneity of the target-less algorithm. The performance of the modified targeted algorithm performed similarly to the target-less algorithm. Based on these results, it was concluded that the targeted color calibration was superior to the target-less algorithm.

Place, publisher, year, edition, pages
2018. , p. 102
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:miun:diva-33876Local ID: DT-V18-G3-010OAI: oai:DiVA.org:miun-33876DiVA, id: diva2:1221775
Subject / course
Computer Engineering DT1
Educational program
Master of Science in Engineering - Computer Engineering TDTEA 300 higher education credits
Supervisors
Examiners
Available from: 2018-06-20 Created: 2018-06-20 Last updated: 2018-06-20Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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