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Digital Image Watermarking Using Sine Transform Technique Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Plant Disease Detection Based on Region-Based Segmentation and KNN Classifier

Authors : Jaskaran Singh, Harpreet Kaur

Published in: Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)

Publisher: Springer International Publishing

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Abstract

The plant disease detection is the technique which can detect disease from the plant leaves. The plant disease detection has various steps which are textural feature analysis, segmentation, and classification. This research paper is based on the plant disease detection using the KNN classifier with GLCM algorithm. In the proposed method, the image is taken as input which is preprocessed, GLCM algorithm is applied for the textural feature analysis, k-means clustering is applied for the region-based segmentation, and KNN classifier is applied for the disease prediction. The proposed technique is implemented in MATLAB and simulation results show up to 97% accuracy.

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previous chapter A Study on Comparative Analysis of Automated and Semiautomated Segmentation Techniques on Knee Osteoarthritis X-Ray Radiographs
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Metadata
Title
Plant Disease Detection Based on Region-Based Segmentation and KNN Classifier
Authors
Jaskaran Singh
Harpreet Kaur
Copyright Year
2019
Book
Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)

Print ISBN: 978-3-030-00664-8

Electronic ISBN: 978-3-030-00665-5

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-00665-5_154