Classification of the grape varieties based on leaf recognition by using SVM classifier [Destek Vektör Makinalari Kullanilarak Yaprak Tanima ile Üzüm Çeşitlerinin Siniflandirilmasi]

Abstract

In this paper, to classify the grape tree species, the extracted features from leaf images are classified using a multi-class support vector machines. Feature extraction stage, the grape leafs are calculated by using 9 different features. Image processing stage involves gray tone dial, median filtering, contrast, thresh holding and morphological-logical processes. In the classification stage, the obtained properties with the help of multi-class support vector machines (MCSVM) is performed classification process. In the testing phase, by applying the different leaf images is calculated the performance of model. In this study, MATLAB software was used. At the end of the test was determined the total success rate of 90.7%. © 2015 IEEE.