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Dimensionality Reduction for Colour Based Pixel Classification
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
2009 (English)In: Proceedings SSBA 2009: Symposium on Image Analysis, Halmstad, March 18-20 / [ed] Josef Bigun, Antanas Verikas, Halmstad: Halmstad University , 2009, 65-68 p.Conference paper, Published paper (Other academic)
Abstract [en]

In digital images, providing classification based on colour, hue or spectral angle is a problem usually solved by combining a variety of pre-processing steps, as well as object wise classifiers. We have developed a method for transforming colour or multispectral image data to a 1D colour histogram with respect to the digital characteristics of intensity measurements. Classification is then reduced to 1D histogram segmentation which is a simpler problem. The proposed method, based on ideas of spectral decomposition, was previously applied in dual-colour fluorescence microscopy for quantification and detection of colocalization insensitive to cross-talk. In this paper the principle is expanded to unsupervised colour based pixel classification algorithms in hue-saturation-lightness or luminance-chrominance colour spaces.

Place, publisher, year, edition, pages
Halmstad: Halmstad University , 2009. 65-68 p.
Keyword [en]
color image analysis, human skin color, face detection, fluorescence microscopy, cross talk, dimensionality reduction
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Analysis
Identifiers
URN: urn:nbn:se:uu:diva-111371ISBN: 978-91-633-3924-0 (print)OAI: oai:DiVA.org:uu-111371DiVA: diva2:280827
Conference
Swedish Symposium in Image Analysis (SSBA) 2009
Projects
EU-Strep project ENLIGHT (ENhanced LIGase based Histochemical Techniques)
Available from: 2009-12-14 Created: 2009-12-11 Last updated: 2010-11-29Bibliographically approved

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