Author : Miss.Pratiksha Yadav and Prof. Prashant Ahire

The use of computers in many engineering fields is widely accepted. The field of geotechnical engineering is not far behind. The use of computers not only automates the process of soil classification, but also makes it more objective. The chances of human error are minimized, thus saving a lot of energy, time and most importantly, money. Identification of the soil type helps to avoid agricultural product quantity loss. A classification for engineering purpose should be based mainly on mechanical properties. This work explains support vector machine based classification of the soil types. Soil classification includes steps like image acquisition, image preprocessing, feature extraction and classification. The color features, edge detection features and texture features of soil images are extracted. Using support vector machine (SVM) classifies the soil features to find the type of soil. Using the final soil type we can recommend which crop is suitable for this type of soil.

Keywords: Image preprocessing, Feature Extraction, EdgeDetection, Texture Features, SVM