Title

A Leaf Recognition Approach to Plant Classification Using Machine Learning

Document Type

Conference Paper

Publication Date

12-3-2018

Publication Source

Proceedings of the IEEE National Aerospace Electronics Conference, NAECON

Abstract

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.

Inclusive pages

431-434

ISBN/ISSN

0547-3578

Publisher

IEEE

Keywords

component, formatting, insert, style, styling, University of Dayton Electro-optics and Photonics


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