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DOI Prefix: 10.47001/IRJIET

Plant Leaf Disease Feature Extraction Centered on Intensity Permanence

Dr. Shanmuga Rajathi DSchool of Computer Studies-PG, Rathnavel Subramaniam (RVS) College of Arts and Science, Coimbatore, Tamilnadu, IndiaDr. K ChitraSchool of Computer Studies-PG, Rathnavel Subramaniam (RVS) College of Arts and Science, Coimbatore, Tamilnadu, India

Vol 7 No 12 (2023): Volume 7, Issue 12, December 2023 | Pages: 177-181

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 26-12-2023

doi Logo doi.org/10.47001/IRJIET/2023.712025

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Abstract

The primary organ of the plant, the leaf, is classified automatically using image processing methods. During processing, the leaf images' features are taken out and used for categorization. Research on plants and agriculture benefits from the extraction of leaf features. The manual feature extraction process is less structured and involves measuring features like shape symmetry, color, etc. with accuracy. Advancements in image processing techniques offer a productive means of extracting features from images of leaves, and numerous innovative techniques have been put forth in the literature. These studies rely less on human intuition and instead focus on automatically extracting features from images using a variety of algorithms. 

Keywords

Feature Extraction, Leaf, Automatic Detection, Ann, FEBIP


Citation of this Article

Dr. Shanmuga Rajathi D, Dr. K Chitra, “Plant Leaf Disease Feature Extraction Centered on Intensity Permanence” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 12, pp 177-181, December 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.712025

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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