Grain-size assessment of fine and coarse aggregates through bipolar area morphology View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2015-08

AUTHORS

Francesco Bianconi, Francesco Di Maria, Caterina Micale, Antonio Fernández, Richard W. Harvey

ABSTRACT

This paper presents a new methodology for computing grey-scale granulometries and estimating the mean size of fine and coarse aggregates. The proposed approach employs area morphology and combines the information derived from both openings and closings to determine the size distribution. The method, which we refer to as bipolar area morphology (BAM), is general and can operate on particles of different size and shape. The effectiveness of the procedure was validated on a set of 13 classes of aggregates of size ranging from 0.125 to 16 mm and made a comparison with standard, fixed-shape granulometry. In the experiments our model consistently outperformed the standard approach and predicted the correct size class with overall accuracy over 92 %. Tests on three classes from real samples also confirmed the potential of the method for application in real scenarios. More... »

PAGES

775-789

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00138-015-0692-z

DOI

http://dx.doi.org/10.1007/s00138-015-0692-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1017997523


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