Estimation of Critical Parameters in Concrete Production Using Multispectral Vision Technology
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.
KeywordsLight Emit Diode Critical Parameter Multispectral Image Canonical Discriminant Analysis Concrete Production
- 1.Mindess, S., Young, J.F.: Concrete. Prentice-Hall, Inc., Englewood Cliffs (1981)Google Scholar
- 2.Rixom, M.R., Mailuaganam, N.P.: Chemical Admixtures for Concrete. R. & F.N. Spon, NY (1986)Google Scholar
- 3.Fisher, R.A.: The use of multiple measurements in taxonomic problems. Annals of Eugenics 7, 179–188 (1936)Google Scholar
- 7.Lattin, J., Carroll, J.D., Green, P.E.: Analyzing Multivariate Data. Brooks/Cole, Monterey (2003)Google Scholar