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Open Access
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Janhavi Borkar,, Shrishti Kamanboina, Satyam Bhalerao,, Mugdha A. Kango,
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- Student, Department of Electronic and Telecommunication,, Student, Department of Electronic and Telecommunication,, Student, Department of Electronic and Telecommunication,, Student, Department of Electronic and Telecommunication, PES Modern College of Engineering,, PES Modern College of Engineering,, PES Modern College of Engineering, PES Modern College of Engineering Pune Maharashtra,, Pune Maharashtra,, Pune Maharashtra,, Pune Maharashtra, India, India, India, India
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Abstract
nThis research presents an overview of different image processing techniques for the identification of leaf disease. Many algorithms can be used to identify and categorize leaf diseases in plants, and digital image processing provides a quick, dependable, and accurate method of disease detection. This paper presents various techniques used on multiple crops and the achieved accuracy for each model. Leaf disease detection is a critical task in agriculture to ensure the health and productivity of crops. Traditional methods of disease identification are often labor-intensive and subjective, highlighting the need for automated solutions. In recent years, deep learning techniques have emerged as powerful tools for automatic disease detection, offering the potential to revolutionize agricultural practices. Our work primarily focuses on analyzing several methods for detecting leaf disease and presents a summary of various image-processing methods. When given the resources and information required for early disease identification, farmers are more equipped to make informed decisions and act swiftly to prevent it. As a result, their total crop yield and income can rise. From the review we conclude that convolutional neural network models show the most accurate results with highest accuracy scores and are best suited for image processing because they employ the technique known as parameter sharing that makes them more structured while working with image data.
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Keywords: Image processing, leaf disease, agriculture, pesticides, crop
n[if 424 equals=”Regular Issue”][This article belongs to Current Trends in Signal Processing(ctsp)]
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References
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| Volume | 14 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 01 | |
| Received | April 23, 2024 | |
| Accepted | May 23, 2024 | |
| Published | August 16, 2024 |
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