PLANT DISEASE IDENTIFICATION SYSTEM

Abstract

ABSTRACT A plant disease identification system (100), comprising an image acquisition module (102) configured to capture images of plants in agricultural fields, an image processing module (104) configured to enhance image quality through normalization, noise reduction, and image augmentation, a feature extraction module (106) configured to extract characteristics of plant health, such as color, texture, and morphological features, using convolutional neural networks (CNNs); a machine learning classifier (108) configured to categorize the health state of the plant, the classifier trained on a dataset of labelled plant images, encompassing various plant species and disease types, and a user interface (110) configured to display the diagnosis, including the identified disease and suggested management actions based on classification results, enabling farmers to implement disease management strategies.

Specification

Description:PLANT DISEASE IDENTIFICATION SYSTEM

FIELD OF THE DISCLOSURE
[0001] This invention generally relates to a field of automated agricultural systems and, in particular, to a plant disease identification system using image processing and machine learning techniques to facilitate accurate, real-time diagnosis of plant diseases across diverse agricultural settings.
BACKGROUND

[0002] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
[0003] Agriculture faces significant challenges in managing plant diseases, which can drastically affect crop yi , Claims:1. A plant disease identification system (100), comprising:
an image acquisition module (102) configured to capture images of plants in agricultural fields;
an image processing module (104) configured to enhance image quality through normalization, noise reduction, and image augmentation;
a feature extraction module (106) configured to extract characteristics of plant health, such as color, texture, and morphological features, using convolutional neural networks (CNNs);
a machine learning classifier (108) configured to categorize the health state of the plant, the classifier trained on a dataset of labeled plant images, encompassing various plant species and disease types; and
a user interface (110) configured to display the diagnosis, including the identified disease and suggested management actions based on classification results, enabling farmers to implement disease management strategies.

2. The plant disease identification system (100) as claimed in claim 1, wherein the image processing module (104) fu

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