Abstract.
We analyze images of concrete aggregate material and design computational measures for angularity, surface texture, and the shape of the particles. The features obtained with image analysis are used as additional explanatory variables in statistical models for predicting the quality properties of concrete. Model comparison confirms that the image analysis features improve predictions.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Bernardo JM, Smith AFM (1994) Bayesian theory. Wiley, New York
Järvenpää H (2001) Quality characteristics of fine aggregates and controlling their effects on concrete. Acta Polytechnica Scandinavica, Civil Engineering and Building Construction Series No. 122. Finnish Academy of Technology, Helsinki
Masad E, Button JW (2000) Unified imaging approach for measuring aggregate angularity and texture. Comput Aided Civil Infrastruct Eng 15(4):273-280
Neal RM (1996) Bayesian learning for neural networks. Springer, Berlin Heidelberg New York
Neal RM (1997) Monte Carlo implementation of Gaussian process models for Bayesian regression and classification. Technical Report 9702, Dept. of Statistics, University of Toronto
Neal RM (1999) Regression and classification using Gaussian process priors (with discussion). In: Bernardo JM, Berger JO, Dawid AP, Smith AFM (eds) Bayesian statistics 6. Oxford University Press, Oxford, UK, pp 475-501
Spiegelhalter DJ, Best NG, Carlin BP, van der Linde A (2002) Bayesian measures of model complexity and fit (with discussion). J R Stat Soc Ser B Stat Methodol 64(3):583-639
Tuceryan M, Jain A (1993) Texture analysis. In: Chen C, Pau L, Wang P (eds) Handbook of pattern recognition and vision. World Scientific, Singapore, pp 235-276
Vehtari A (2001) Bayesian model assessment and selection using expected utilities. PhD dissertation, Helsinki University of Technology
Vehtari A, Lampinen J (2001) On Bayesian model assessment and choice using cross-validation predictive densities. Technical Report B23, Helsinki University of Technology, Laboratory of Computational Engineering
Vehtari A, Lampinen J (2002) Bayesian model assessment and comparison using cross-validation predictive densities. Neural Comput 14(10):2439-2468
Vehtari A, Lampinen J (2003) Expected utility estimation via cross-validation. In: Bernardo JM, Bayarri MJ, Berger JO, Dawid AP, Heckerman D, Smith AFM, West M (eds) Bayesian statistics 7. Oxford University Press, Oxford, UK, pp 701-710
Author information
Authors and Affiliations
Corresponding author
Additional information
Received: 12 May 2004, Accepted: 1 October 2004, Published online: 10 February 2005
Correspondence to: Ilkka Kalliomäki
Rights and permissions
About this article
Cite this article
Kalliomäki, I., Vehtari, A. & Lampinen, J. Shape analysis of concrete aggregates for statistical quality modeling. Machine Vision and Applications 16, 197–201 (2005). https://doi.org/10.1007/s00138-004-0172-3
Issue Date:
DOI: https://doi.org/10.1007/s00138-004-0172-3