Utilizing Image Processing Techniques for Soil Particle Sizing
Document Type : Research Paper
Authors
- 1 M.Sc. Alumnus, Department of Civil Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Kurdistan, Iran
- 2 Assist. Professor, Department of Civil Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Kurdistan, Iran
- 3 M.Sc. Alumnus, Department of Earthquake Engineering, Building and Housing Research Center, Road, Housing and Urban Development Research Center, Tehran, Iran
Abstract
Counting the number of soil particles in grain size studies is of great importance, especially in geological, agricultural, environmental, and engineering sciences. It can be used for detailed analysis of soil properties, determining soil structure, and environmental analysis. The main goal of this research is to evaluate the grain size and shape recognition of soil particles using image processing techniques. In this study, initially, color images of soil grain size were acquired. Then, they were processed using Python programming language and the Scikit-Image library. Finally, for model validation, 17 rice grains and 8 coins were used. The results demonstrated that this method was able to accurately detect the number and shape of these particles. It also performed well in identifying the number and shape of soil particles. Furthermore, when compared to several other software tools in the same field, it provided better results. This approach can be utilized to plot the soil grain size curve, ultimately leading to reduced computational costs and time.
Keywords
Subjects
Hydraulic and river engineering
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