A Leaf Recognition Approach to Plant Classification Using Machine Learning

The identification of plants is a very important component of workflows in plant ecological research. This paper presents an automated leaf recognition method for plant identification. The proposed technique is simple and computationally efficient. It is based on a combination of two types of texture features, named Bag-of-features (BOF) and Local Binary Pattern (LBP). These features are utilized as inputs to a decision-making model that is based on a multiclass Support Vector Machine (SVM) classifier. The introduced method is evaluated on a publicly available leaf image database. The experimental results demonstrate that our proposed method is the highly efficient technique for plant recognition.