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Authors: Juha Lehtonen 1 ; Jussi Parkkinen 1 ; Timo Jaaskelainen 2 and Alexei Kamshilin 3

Affiliations: 1 Department of Computer Science and Statistics, University of Joensuu, Finland ; 2 Department of Physics and Mathematics, University of Joensuu, Finland ; 3 Department of Physics, University of Kuopio, Finland

ISBN: 978-989-8111-69-2

Keyword(s): Color spectrum, Eigenvector, Filtering, Illuminant, Sampling interval.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Feature Extraction ; Features Extraction ; Image and Video Analysis ; Image Filtering ; Image Formation and Preprocessing ; Image Quality ; Informatics in Control, Automation and Robotics ; Signal Processing, Sensors, Systems Modeling and Control ; Statistical Approach

Abstract: Eigenvectors from Standard Object Colour Spectra (SOCS) set were used with several other spectra sets to find the optimal sampling intervals for optimal number of eigenvectors. The sampling intervals were calculated for each eigenvector separately. The analysis was applied not only for different sets of reflectance spectra, but also for spectra sets under different real light sources and standard illuminations. It is shown that 20 nm sampling interval for eigenvectors from SOCS set can be used for reflectance data and data under such light sources which spectrum is smooth. However, data under peaky real fluorescent light sources and standard F-illuminant require accurate 5 nm or even narrower sampling interval for the first few eigenvectors, but can be wider with some of the others. These eigenvectors from SOCS set are shown to be applicable for the other data sets. The results give guidelines for the required accuracy of eigenvectors under different light sources that can be consider ed e.g. in eigenvector-based filter design. (More)

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Paper citation in several formats:
Lehtonen J.; Parkkinen J.; Jaaskelainen T.; Kamshilin A. and (2009). EIGENVECTOR ANALYSIS FOR OPTIMAL FILTERING UNDER DIFFERENT LIGHT SOURCES.In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 95-100. DOI: 10.5220/0001798700950100

@conference{visapp09,
author={Juha Lehtonen and Jussi Parkkinen and Timo Jaaskelainen and Alexei Kamshilin},
title={EIGENVECTOR ANALYSIS FOR OPTIMAL FILTERING UNDER DIFFERENT LIGHT SOURCES},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009)},
year={2009},
pages={95-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001798700950100},
isbn={978-989-8111-69-2},
}

TY - CONF

JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2009)
TI - EIGENVECTOR ANALYSIS FOR OPTIMAL FILTERING UNDER DIFFERENT LIGHT SOURCES
SN - 978-989-8111-69-2
AU - Lehtonen, J.
AU - Parkkinen, J.
AU - Jaaskelainen, T.
AU - Kamshilin, A.
PY - 2009
SP - 95
EP - 100
DO - 10.5220/0001798700950100

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