Rough Set based SVM Technique for Spatial Image Classification

摘要

There exist many traditional spatial image classification techniques which are developed over past years and exists in literature. Today, expert systems and machine learning methods are getting popularity in this area because of the effective classification. In this paper, Rough set based Support vector machine classification method (RS-SVM) is proposed. In this technique, Rough set (RS) is used as a feature selection mathematical tool which eliminates the redundant features. Further, this reduced dimensionality data set is given to Support vector machine (SVM) classifier. This process improves the classification accuracy and performance. We have performed experiments using standard geospatial images for above-proposed method for classification.