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A Study of Emerging Image Processing and Machine Learning Methodologies for Classification of Plant Leaf Disease


Affiliations
1 Department of Electronics & Communication Engineering, Dr. SMCE, Bangalore, Karnataka-562132, India
2 Department of Electronics & Communication Engineering, SIET, Tumakuru, Karnataka-572106, India
 

Agriculture and productivity are extremely important to a country's economy. Plants becoming infected with diseases are a natural occurrence, but it can result in significant losses in agricultural productivity if sufficient precautions are not taken to identify the disease and apply certain pesticides in a timely manner. As a result, it's critical to have certain automated ways for detecting plant leaf diseases that save time and effort. Many people presented a number of automated approaches to detect and classify plant leaf diseases with varying levels of accuracy due to developments in image processing and machine learning techniques. In this study, we examine a number of current strategies that have been developed in this field. As a result, we may draw conclusions about the performances and what further improvements can be made to design more efficient systems in the future.

Keywords

Fuzzy Logic, Gray Level Co-Inference Matrix, Image Processing, Machine Learning, Plant Leaf Disease.
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  • A Study of Emerging Image Processing and Machine Learning Methodologies for Classification of Plant Leaf Disease

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Authors

Asif Hassan
Department of Electronics & Communication Engineering, Dr. SMCE, Bangalore, Karnataka-562132, India
Lokesh B S
Department of Electronics & Communication Engineering, SIET, Tumakuru, Karnataka-572106, India

Abstract


Agriculture and productivity are extremely important to a country's economy. Plants becoming infected with diseases are a natural occurrence, but it can result in significant losses in agricultural productivity if sufficient precautions are not taken to identify the disease and apply certain pesticides in a timely manner. As a result, it's critical to have certain automated ways for detecting plant leaf diseases that save time and effort. Many people presented a number of automated approaches to detect and classify plant leaf diseases with varying levels of accuracy due to developments in image processing and machine learning techniques. In this study, we examine a number of current strategies that have been developed in this field. As a result, we may draw conclusions about the performances and what further improvements can be made to design more efficient systems in the future.

Keywords


Fuzzy Logic, Gray Level Co-Inference Matrix, Image Processing, Machine Learning, Plant Leaf Disease.

References