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Performance of SVM Classifier For Image Based Soil Classification

Publication Type : Conference Paper

Publisher : International conference on Signal Processing, Communication, Power and Embedded System (SCOPES)-2016

Source : International conference on Signal Processing, Communication, Power and Embedded System (SCOPES)-2016, 2016.

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2016

Abstract : 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.

Cite this Research Publication : Dr. Padmavathi S. and .K, S., “Performance of SVM Classifier For Image Based Soil Classification”, in International conference on Signal Processing, Communication, Power and Embedded System (SCOPES)-2016, 2016.

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