Estimation of Critical Parameters in Concrete Production Using Multispectral Vision Technology |
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| 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. |
| Keywords | image analysis; critical parameters; concrete; water content; size distribution; type; aggregate |
| Type | Conference paper [With referee] |
| Conference | Lecture Notes in Computer Science, LNCS3540 |
| Year | 2005 pp. 1228-1237 |
| Publisher | Informatics and Mathematical Modelling, Technical University of Denmark, DTU |
| Address | Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby |
| Series | Lecture Notes in Computer Science |
| BibTeX data | [bibtex] |
| IMM Group(s) | Image Analysis & Computer Graphics |