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Plant Disease Diagnosis for Smart Phone Applications with Extensible Set of Diseases

Computer Science and Engineering Department, University of Thessaly, 41110 Larissa, Greece
Appl. Sci. 2019, 9(9), 1952; https://doi.org/10.3390/app9091952
Received: 4 March 2019 / Revised: 25 April 2019 / Accepted: 10 May 2019 / Published: 13 May 2019
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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Abstract

A plant disease diagnosis method that can be implemented with the resources of a mobile phone application, that does not have to be connected to a remote server, is presented and evaluated on citrus diseases. It can be used both by amateur gardeners and by professional agriculturists for early detection of diseases. The features used are extracted from photographs of plant parts like leaves or fruits and include the color, the relative area and the number of the lesion spots. These classification features, along with additional information like weather metadata, form disease signatures that can be easily defined by the end user (e.g., an agronomist). These signatures are based on the statistical processing of a small number of representative training photographs. The extracted features of a test photograph are compared against the disease signatures in order to select the most likely disease. An important advantage of the proposed approach is that the diagnosis does not depend on the orientation, the scale or the resolution of the photograph. The experiments have been conducted under several light exposure conditions. The accuracy was experimentally measured between 70% and 99%. An acceptable accuracy higher than 90% can be achieved in most of the cases since the lesion spots can recognized interactively with high precision. View Full-Text
Keywords: plant disease; smart phone application; image processing; classification; segmentation; citrus diseases plant disease; smart phone application; image processing; classification; segmentation; citrus diseases
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Petrellis, N. Plant Disease Diagnosis for Smart Phone Applications with Extensible Set of Diseases. Appl. Sci. 2019, 9, 1952.

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