Performance of SVM classifier for image based soil classification

Classification of soil is the dissolution to soil sets to particular group having a like characteristics and similar manners. Almost all countries do product exporting, in which those countries exporting higher agricultural product are very much depend on the soil characteristics. Thus, soil characteristics identification and classification is very much important. 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 paper explains support vector machine based classification of the soil types. Soil classification includes steps like image acquisition, image preprocessing, feature extraction and classification. The texture features of soil images are extracted using the low pass filter, Gabor filter and using color quantization technique. Mean amplitude, HSV histogram, Standard deviation are taken as the statistical parameters.

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