Combined Classifier for Plant Classification and Identification from Leaf Image Based on Visual Attributes

Several methods have been proposed so far for plant classification based on leaf image. Generally, the methods don't include all the physical attributes of the leaf which entails important information. In this paper, various characteristics shape, color, texture and vein have been computed which resulted in more reliable results. The identification of plant's category of input images has been accomplished along with the classification of various plants into their respective categories. In this case, combined classifier using majority voting technique has been proposed for recognizing leaf's category along with SVM, Naïve Bay's and Decision tree classifiers. The experimental results shows that combined classifier outperforms the performance of SVM, Naïve Bay's and Decision tree classifiers.