@CONFERENCE\{IMM2005-03653,
    author       = "M. E. Hansen and B. K. Ersb{\o}ll and J. M. Carstensen and A. A. Nielsen",
    title        = "Estimation of Critical Parameters in Concrete Production Using Multispectral Vision Technology",
    year         = "2005",
    keywords     = "image analysis; critical parameters; concrete; water content; size distribution; type; aggregate",
    pages        = "1228-1237",
    booktitle    = "Lecture Notes in Computer Science, LNCS3540",
    volume       = "",
    series       = "Lecture Notes in Computer Science",
    editor       = "",
    publisher    = "Informatics and Mathematical Modelling, Technical University of Denmark, {DTU}",
    organization = "",
    address      = "Richard Petersens Plads, Building 321, {DK-}2800 Kgs. Lyngby",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/3653-full.html",
    abstract     = "We analyze multispectral reflectance images of concrete aggregate material, and design computational measures of the important and critical parameters used in concrete production. The features extracted from the images are exploited as explanatory variables in regression models and used to predict aggregate type, water content, and size distribution. We analyze and validate the methods on five representative aggregate types, commonly used in concrete production. Using cross validation, the generated models proves to have a high performance in predicting all of the critical parameters."
}