Matlab Code for Soil Classification
In this project, soil classification is the need of hours for many geotechnical applications. Some amount of primary information regarding the type and structure of the soil.
In this paper, the conventional techniques of soil classification are studied and an image processing-based efficient classifier for soil classifier has been developed and tested.
Seven classes of soil were studied for classification, namely Clay, Clayey Peat, Clayey Sand, Humus Clay, Peat, Sandy Clay, and Silty Sand. Reliable images of soils? were collected and preprocessed.
The preprocessed images are feature extracted and the data extracted is used to train the Support Vector Machine (SVM) classifier. The developed classifier is then tested for efficient classification and accuracy for each class is obtained. The developed model can be used in the development of applications for real-time soil classification. Matlab Code for Soil Classification