Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/2409

Title: Automated sizing of coarse-grained sediments : image-processing procedures
Authors: Graham, David J.
Reid, Ian
Rice, Stephen P.
Keywords: Grain-size analysis
Mathematical morphology
Segmentation
Bottom-hat
Rivers
Fluvial
Issue Date: 2005
Publisher: © Springer Verlag
Citation: GRAHAM, D.J., RICE, I. and REID, S.P., 2005. Automated sizing of coarse-grained sediments : image-processing procedure. Mathematical Geology, 37 (1), pp.1-28
Abstract: This is the first in a pair of papers in which we present image-processing based procedures for the measurement of fluvial gravels. The spatial and temporal resolution of surface grain-size characterization is constrained by the time-consuming and costly nature of traditional measurement techniques. Several groups have developed image-processing based procedures, but none have demonstrated the transferability of these techniques between sites with different lithological, clast form and textural characteristics. Here we focus on imageprocessing procedures for identifying and measuring image objects (i.e. grains); the second paper examines the application of such procedures to the measurement of fluvially-deposited gravels. Four image-segmentation procedures are developed, each having several internal parameters, giving a total of 416 permutations. These are executed on 39 images from three field sites at which the clasts have contrasting physical properties. The performance of each procedure is evaluated against a sample of manually digitized grains in the same images, by comparing three derived statistics. The results demonstrate that it is relatively straightforward to develop procedures that satisfactorily identify objects in any single image or a set of images with similar sedimentary characteristics. However, the optimal procedure is that which gives consistently good results across sites with dissimilar sedimentary characteristics. We show that neighborhood-based operations are the most powerful, and a morphological bottom-hat transform with a double threshold is optimal. It is demonstrated that its performance approaches that of the procedures giving the best results for individual sites. Overall, it out-performs previously published, or improvements to previously published, methods.
Description: This article was published in the journal, Mathematical geology [© Springer Verlag] and is also available at: http://www.springerlink.com/openurl.asp?genre=journal&issn=0882-8121
URI: https://dspace.lboro.ac.uk/2134/2409
ISSN: 0882-8121
1573-8868
Appears in Collections:Published Articles (Geography)

Files associated with this item:

File Description SizeFormat
MathGeol_repository.pdfArticle721.21 kBAdobe PDFView/Open
CoverforPDF.pdfCover sheet27.39 kBAdobe PDFView/Open

 

SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.