abstract

A MatLab toolkit forriver bed porosity analysis

Conclusions

UNIVERSITY OF

BRADFORD

METHODOLOGY

This project is a combined experimental/computational modeling studyaiming to provide an optical inspection tool for river bed porositymeasurement.

A MatLab image analysis software code is developed to processscanned images of gravel soil samples, detect edges of particles[7],calculate valuable statistics[3], find number of objects[7], recognizeshapes of gravels[2], plot Particle Size Distribution curve[7] and calculatethe porosity of the ground sample.

The results from the image analysis procedure are successfullycompared with theoretical values found in literature[1] and wereexpected for corresponding types of soil, and together with otherchecks the accuracy of the model to calculate porosity values fromsimple scans is estimated. The most important of these checks is thecomparison with the experimental results that have been carried out toestimate real porosity values of specific gravel types and gave anestimation of 95% accuracy to the used methods.

The optical software inspection of porosity is of great interest[1] in riverand structural engineering.

Keywords: Porosity; Particle Size Distribution; Grain size analysis;MatLab; Image analysis; gravel river bed; Color edge detection;laboratory flume experiments.

The results of the developed model are checked for their accuracy, comparing with theoreticalvalues[1], with optical confirmation[7], comparing with experimental data[6] and other methods.

references

experiments

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Flo

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big gravel

mixed gravel

SCHOOL OF ENGINEERINGDESIGN AND TECHNOLOGYDEPARTMENT OF CIVIL ANDSTRUCTURAL ENGINEERING Processed by: Angelos Ploumis (09012596)

Supervised by: Dr Tim GoughBradford, May 2011

• Open image with MatLab image analysis toolbox and transform it into table (MxN pixels)

• Make image Grayscale using the applicable threshold.

• Remove noise and fill the gaps that are results of discontinuing areas, shadows, etc.

• Detect boundaries of particles and display them plotted for check from user.

• Calculate and display particle statistics. (Number of objects, image size in pixels, areas of particles, etc).

• Work with individual object, find average sized particle to compare with PSD curve peak.

• Calculate the porosity of the sample of soil.

ImageSize: [1736 2816]NumObjects: 772soil = 'Gravel'

>> porosity = BlackPixels/TotalPixels*100;

porosity = 19.3487

• Produce the particle size distribution curve and define soil classification.

Graph 1: Comparative graphical presentation of the different data for flows vs time observed during the experiments.

experimentPorosity

errormodel experiment

#1 small 18.3 % 14 % 4.3 %

#2 big 32.9 % 28 % 4.9 %

#3 mixed 20.1 % 19 % 1.1%

Table 2: Comparison of model results fortwo images of same soil captured fromdifferent height.

Table 1: Comparison of the experimentalvs the model results for the porosity.

test image PSD curve porosity

A 21.4 %

B 24.8 %

MATLAB MODEL STEPS [2] [3] [4] [7]

Figures: Exported images from MatLab image analysis are helpful to optically confirm the results during procedure.

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Graph 2: Particle Size Distribution

size of particle (mm)

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Seven sets of laboratory experiments[5] were conducted in a re-circulating water flume to determine the porosity of the gravelmaterial[6] spread on the bed of the flume.Three different types of gravels were used. “Small” gravels with averagediameter about 10 mm, “Big” gravels with average diameter about 20mm, and “Mixed” Gravels with a mixture of the two previous types ofgravels in random analogy.

Acknowledgements: I would like to express my gratitude to my supervisor, Dr Tim Gough, for his valuablesupport and expert advice during all the process of the project implementation, the theoretical direction, thesoftware development and the laboratory work. Also, many thanks to Dr Leigh Mulvaney-Johnson and Dr H.S.Rajamani for their valuable help in the development of the MatLab code and their precious ideas. This project isdedicated to my friends and family who helped in their own way.

The data and measurements observed in the laboratory experiments produce[5] the following graph in which it is possible to observe the comparative difference of the flows for different mediums and their difference with the “datum” flow (only water).

These differences are transformed [6] into percentile changes of volumes (pores of medium or total volume for datum) and give the way for calculation of the porosity of the bedform.

VQ

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[1] Church, M.A. (1987), River bed gravels: Sampling and analysis, Wiley-Interscience

[2] Demirkaya, O. (2009), Image Processing with MATLAB, Taylor & Francis/CRC

[3] Trauth, M.H. (2006), MATLAB recipes for earth sciences, Springer

[4] McMahon, D. (2007), MATLAB demystified, McGraw-Hill

[5] Lomax, W.R. (1980), Laboratory work in Hydraulics, Richard Clay Ltd

[6] Bear, J.J (2010), Groundwater and Aquifers, Modeling Groundwater Flow, Theory and Applications of Transport in Porous Media, 23: p. 65-80

[7] Mathworks, Inc (2010), MATLAB Image Processing Toolbox User’s Guide, available from: http://www.mathworks.com/help/toolbox/images/

• Model vs Experimental results showa relativity of 95%.

• The comparison of the results showsgreat accuracy with an error of 3.4%.• The Particle Size Distribution curveshave the same shape and peaks insame number (average particle size).• The differences in porosity resultsand PSD curves are caused by thechange in image definition. Particlesless than 300 pixels are removed.