Vermiculate artefacts in image analysis of granular materials |
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| Institution: | 1. School of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China;2. Key Laboratory of Roads and Railway Engineering Safety Control of Ministry of Education, Shijiazhuang Tiedao University, Shijiazhuang 050043, China;3. The Key Laboratory for Health Monitoring and Control of Large Structures in Hebei Province, Shijiazhuang Tiedao University, Shijiazhuang 050043, China;4. State Key Laboratory of Frozen Soils Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China;1. Universidade Federal do Paraná, PG-MEC, Centro Politécnico, 81.531-990 Curitiba, PR, Brazil;2. Universidade Federal do ParanáPR, CNPq, Centro Politécnico, 81.531-990 Curitiba, Brazil;3. Universidade Tecnológica Federal do Paraná, CNPq 81.531-990 Curitiba, PR, Brazil;4. Universidade Tecnológica Federal do Paraná, PPGEM, 80.230.901 Curitiba, PR, Brazil |
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| Abstract: | Some reported analyses of images of deforming granular materials have generated surprising vermiculate strain features which are difficult to reconcile with the mechanics of deformation of granular matter. Detailed investigation using synthetic images and improved processing of images of laboratory experiments indicates that such features can emerge as a consequence of the image acquisition (sensor, contrast, resolution), the subsequent image correlation implementation, and the user’s choice of processing parameters. The two principal factors are: (i) the texture and resolution of the images and (ii) the algorithm used to achieve sub-pixel displacement resolution. Analysis of the images using a sub-pixel interpolation algorithm that is more robust than that used originally eliminates the vermiculate features for images with moderate resolution and texture. However, erroneous features persist in images with low resolution and poor texture. Guidance is provided on ways in which such artefacts can be avoided through improved experimental and image analysis techniques. |
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| Keywords: | Granular materials Digital image correlation Vermiculation Sub-pixel interpolation |
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