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Texture-based estimation of physical characteristics of sand grains

Newell, AJ; Griffin, LD; Morgan, RM; Bull, PA; (2011) Texture-based estimation of physical characteristics of sand grains. In: Proceedings: 2010 Digital Image Computing: Techniques and Applications: DICTA 2010 1-3 December 2010, Sydney, Australia. (pp. pp. 504-509). IEEE Computer Society: Piscataway, US. Green open access

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Abstract

The common occurrence and transportability of quartz sand grains make them useful for forensic analysis, providing that grains can be accurately and consistently designated into prespecified types. Recent advances in the analysis of surface texture features found in scanning electron microscopy images of such grains have advanced this process. However, this requires expert knowledge that is not only time intensive, but also rare, meaning that automation is a highly attractive prospect if it were possible to achieve good levels of performance. Basic Image Feature Columns (BIF Columns), which use local symmetry type to produce a highly invariant yet distinctive encoding, have shown leading performance in standard texture recognition tasks used in computer vision. However, the system has not previously been tested on a real world problem. Here we demonstrate that the BIF Column system offers a simple yet effective solution to grain classification using surface texture. In a two class problem, where human level performance is expected to be perfect, the system classifies all but one grain from a sample of 88 correctly. In a harder task, where expert human performance is expected to be significantly less than perfect, our system achieves a correct classification rate of over 80%, with clear indications that performance can be improved if a larger dataset were available. Furthermore, very little tuning or adaptation has been necessary to achieve these results giving cause for optimism in the general applicability of this system to other texture classification problems in forensic analysis.

Type: Proceedings paper
Title: Texture-based estimation of physical characteristics of sand grains
Event: 2010 Digital Image Computing: Techniques and Applications: DICTA 2010
ISBN-13: 9781424488162
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/DICTA.2010.91
Publisher version: http://dx.doi.org/10.1109/DICTA.2010.91
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Histograms, Forensics, Scanning electron microscopy, Image coding, Energy states, Geophysical measurement techniques, Ground penetrating radar
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science
URI: https://discovery.ucl.ac.uk/id/eprint/1308978
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