A Review on Fruit and Leaf Disease Detection Using Various Image Processing Approaches


A Review on Fruit and Leaf Disease Detection Using Various Image Processing Approaches

Khushbu kumari, Neelesh Jain, Bity Merin Anish

Khushbu kumari, Neelesh Jain, Bity Merin Anish "A Review on Fruit and Leaf Disease Detection Using Various Image Processing Approaches" Published in International Journal of Trend in Research and Development (IJTRD), ISSN: 2394-9333, Volume-10 | Issue-4 , August 2023, URL: http://www.ijtrd.com/papers/IJTRD27007.pdf

This article reviews several image processing methods for detecting leaf disease. Digital image processing can quickly identify and categorize plant leaf diseases. The study uses artificial neural networks (ANNs) and clustering to classify diseases (used by several authors). Currently, we're investigating new ways to identify leaf disease and image processing techniques. This article also discusses how fruit disease causes economic and agricultural losses. Detecting sick fruit was formerly done manually, but advances in technology have enabled picture processing. There are two stages: training and testing. To identify whether the fruit is sick, and if so, which illness, all data related to infected and non-infected fruit is stored throughout the training phase. This article describes the current techniques for identifying tainted fruit. These techniques help growers identify fruit diseases early on.

SVM, segmentation, leaf diseases, fuzzy logic, feature extraction, morphological processing CCV, K-means Clustering, LBP, SVM, and Back Propagation Neural Networks.


Volume-10 | Issue-4 , August 2023

2394-9333

IJTRD27007
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