A New Feature Based Algorithm for Image Analysis of Deformable Materials for Laboratory Investigations of Slope Stability

• Published in: Geotechnical and geological engineering Vol. 36; no. 2; pp. 1059 - 1069
• Main Authors: Elmouttie, Marc, Olsson, Andrew, Khanal, Manoj, Hoehn, Karsten, Adhikary, Deepak
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.04.2018; Springer Nature B.V
• Subjects: Algorithms; Analysis; Civil Engineering; Computer simulation; Constraint modelling; Data analysis; Deformation; Deformation mechanisms; Detection; Earth and Environmental Science; Earth Sciences; Failure mechanisms; Formability; Geotechnical Engineering & Applied Earth Sciences; Granular materials; Granular media; Hydrogeology; Image analysis; Image processing; Laboratories; Modelling; Original Paper; Outliers (statistics); Particle image velocimetry; Particle tracking; Robustness (mathematics); Slope stability; Stability analysis; Terrestrial Pollution; Velocity measurement; Waste Management/Waste Technology; Slope stability; Particle image velocimetry; Image analysis; Sand grain tracking
• ISSN: 0960-3182; 1573-1529
• DOI: 10.1007/s10706-017-0375-9

Physical modelling of slope stability scenarios can provide new insights into failure mechanisms as well as assistance with interpretation of numerical modelling investigations. To increase the value of such experiments, algorithms that support rapid analysis and quantification of the slope deformation occurring in the experiment are needed. Feature based image analysis has advantages in this respect over area or patch based approaches but suffers from robustness issues. To this end, a new image processing algorithm for measurement of deformation of granular media in laboratory experiments is presented. Our novel algorithm combines a feature detector with model based constraints and outlier detection to achieve fast and robust particle tracking. Comparison with a high precision particle image velocimetry algorithm shows excellent results with much improved processing times. Application of the algorithm for analysis of a laboratory simulation of slope stability is demonstrated and comparison with numerical modelling confirms the algorithm’s flexibility and robustness.