Leaf Classification Using Machine Learning Algorithms

Abstract

On earth plants play an essential role for all living beings. A part of plants is leaf. Plant leaves are classified technically. Different morphological features has been supported for leaf assessment & classification. Some successful classification techniques are Linear Regression, KNearest Neighbor Classifier, Support Vector machine and so on. To find the standardness of the results various data sets have been used which are completely different. That's why picking the strategy for classification is not an easy task at all. Biology, Ayurveda, Agriculture etc are various fields where plant leaf classifications are used. In this paper, three datasets have been collected to classify leaf. Here the leaf images were extracted by applying relevant leaf image extraction methods. In the extracted images, there are three values which are margin, shape and texture. Then the dataset is preprocessed and different machine learning classifiers are trained. Finally, the classification test is carried out to achieve leaf classification accuracy and efficiency. Based on accuracy ,comparingwith three datasets Random Forest classifier performs better among different machine learning methods

Keywords

• leaf classification
• svm
• random forest classifier
• pipeline
• standardscaler