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2021 | OriginalPaper | Chapter

Plant Disease Recognition Based on Multi-dimensional Features of Leaf RGB Images

Authors : Basim Al-Windi, Vladimir Tutygin

Published in: Proceedings of International Scientific Conference on Telecommunications, Computing and Control

Publisher: Springer Singapore

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Abstract

A system based on the representation of sets of texture parameters of Haralik as multi-dimensional vectors, including the stages of normalizing leaf images, training, testing, recognition. The training stage includes geometric and parametric normalization of the source photo images, calculation of GLCM adjacency matrices, matrix of estimates of mathematical expectations and confidence intervals of the scatter of the Haralik parameters of the components R, G, B, RG, RB, GB of the source RGB photo images; the testing phase, performed by modeling statistical tests in order to determine the required quantity averaging parameters of the diagnosed photo images; recognition stage, based on a correlation comparison of the column vectors of the matrix of estimates of mathematical expectations with the column vector of the averaged values of the parameters of the diagnosed photo images.

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Metadata
Title
Plant Disease Recognition Based on Multi-dimensional Features of Leaf RGB Images
Authors
Basim Al-Windi
Vladimir Tutygin
Copyright Year
2021
Publisher
Springer Singapore
Book
Proceedings of International Scientific Conference on Telecommunications, Computing and Control

Print ISBN: 978-981-336-631-2

Electronic ISBN: 978-981-336-632-9

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-33-6632-9_5