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2021 | OriginalPaper | Chapter

Identification of Banana Disease Using Color and Texture Feature

Authors : Vandana V. Chaudhari, Manoj P. Patil

Published in: Recent Trends in Image Processing and Pattern Recognition

Publisher: Springer Singapore

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Abstract

Plant diseases have grown-up in agriculture to be an impasse as it can cause dwindling in both quantity and quality of farming yield. This work explains a simple and adept method used to recognize leaf diseases by applying digital image processing and machine learning technology. In this study 24 color feature, 12 shape and 4 texture features were obtained from images of four kinds of diseases like, Sigatoka, Panama Wilt, Bunchy Top and Banana Streak Virus diseases. Principal component analysis (PCA) was achieved for reducing dimensions in features extracted and k-nearest neighbour classifiers used to identify banana diseases. The finest result was obtained when image identification was conducted based on PCA with K-nearest neighbour classifier.

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previous chapter Deformation Behaviour of Soil with Geocell Using Image Analysis Techniques

next chapter Enhanced HOG-LBP Feature Vector Based on Leaf Image for Plant Species Identification

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https://github.com/godliver/source-code-BBW-BBS

Title: Identification of Banana Disease Using Color and Texture Feature
Authors: Vandana V. Chaudhari
Manoj P. Patil
Publisher: Springer Singapore
Book: Recent Trends in Image Processing and Pattern Recognition
Print ISBN: 978-981-16-0492-8

Electronic ISBN: 978-981-16-0493-5

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-981-16-0493-5_21

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