Cell Phone Image-Based Plant Disease Classification

View Sample PDF

Author(s): Marion Neumann (Universtiy of Bonn, Germany), Lisa Hallau (University of Bonn, Germany), Benjamin Klatt (Central Institute for Decision Support Systems in Crop Protection, Germany), Kristian Kersting (TU Dortmund University, Germany)and Christian Bauckhage (University of Bonn and Fraunhofer IAIS, Germany)
Copyright: 2017
Pages: 28
Source title: Biometrics: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-0983-7.ch032

Keywords: Biometrics / Information Science Reference / Medicine & Healthcare / Surveillance Systems

Purchase

View Cell Phone Image-Based Plant Disease Classification on the publisher's website for pricing and purchasing information.

Abstract

Modern communication and sensor technology coupled with powerful pattern recognition algorithms for information extraction and classification allow the development and use of integrated systems to tackle environmental problems. This integration is particularly promising for applications in crop farming, where such systems can help to control growth and improve yields while harmful environmental impacts are minimized. Thus, the vision of sustainable agriculture for anybody, anytime, and anywhere in the world can be put into reach. This chapter reviews and presents approaches to plant disease classification based on cell phone images, a novel way to supply farmers with personalized information and processing recommendations in real time. Several statistical image features and a novel scheme of measuring local textures of leaf spots are introduced. The classification of disease symptoms caused by various fungi or bacteria are evaluated for two important agricultural crop varieties, wheat and sugar beet.

The IRMA Community

Research IRM

Cell Phone Image-Based Plant Disease Classification

Purchase

Abstract

Related Content

IRMA Sponsors