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

Bianconi, Francesco, di Maria, Francesco, Micale, Caterina, Fernández, Antonio and Harvey, Richard ORCID: https://orcid.org/0000-0001-9925-8316 (2015) Grain-size assessment of fine and coarse aggregates through bipolar area morphology. Machine Vision and Applications, 26 (6). pp. 775-789. ISSN 0932-8092

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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 validate on a set of 13 classes of aggregates of size ranging from 0.125mm to 16mm and made a comparison with standard, fixed- shape granulometry. In the experiments our model con- sistently outperformed the standard approach and pre- dicted the correct size class with overall accuracy over 92%. Tests on three classes from real samples also con- firmed the potential of the method for application in real scenarios.

Item Type:	Article
Uncontrolled Keywords:	image analysis,granulometry,area morphology,aggregates
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Interactive Graphics and Audio Faculty of Science > Research Groups > Smart Emerging Technologies
Depositing User:	Pure Connector
Date Deposited:	17 Mar 2016 13:32
Last Modified:	19 Apr 2023 00:42
URI:	https://ueaeprints.uea.ac.uk/id/eprint/57547
DOI:	10.1007/s00138-015-0692-z

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