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Title Estimation and Classification through Regression with Variable Selection amongst Features Extracted from Multi-Spectral Images - Estimation of moisture content in sand & Identification of Penicillium fungi
Author Clemmensen, Line Harder
Supervisor Ersbøll, Bjarne Kjær (Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Institution Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
Thesis level Master's thesis
Year 2006
Abstract This report deals with identification of three different species of Penicillium fungi and estimation of moisture content in sand used to make concrete. Multi-spectral images of 9 or 18 bands are used to analyze samples of sand and fungi, respectively. The project covers the image acquisition of the samples, the identification of Regions Of Interest (ROIs) in the images, the feature extraction from the ROIs, and classification or es-timation based on the extracted features. The number of features extracted is much larger than the number of observations and the dimensionality is therefore a big issue in the analysis of the data. Traditional multivariate, statistical methods for variable selection, decomposition, classification, and regression are compared to newer methods that select variables and/or perform coefficient shrinkage within the regression. Dummy variables are constructed to use the newer methods for classification.
Imprint Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU : DK-2800 Kgs. Lyngby, Denmark
Pages 198
Fulltext
Original PDF imm4488.pdf (19.45 MB)
Admin Creation date: 2006-10-06    Update date: 2012-12-18    Source: dtu    ID: 191682    Original MXD