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A Review of Image Processing and Machine Learning for Plant Leaf Disease Identification
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 185 - Number 20 |
| Year of Publication: 2023 |
| Authors: Prabhjot Kaur, Barinderjit Kaur |
10.5120/ijca2023922883
|
Prabhjot Kaur, Barinderjit Kaur . A Review of Image Processing and Machine Learning for Plant Leaf Disease Identification. International Journal of Computer Applications. 185, 20 ( Jul 2023), 14-16. DOI=10.5120/ijca2023922883
Abstract
One of the main factors affecting crop output reduction globally is plant disease and crop losses must be avoided through early detection of these diseases. Automating the identification of plant diseases has been demonstrated to be highly promising when using image processing and machine learning approaches. In the present work, fusion techniques were utilised to combine data from several sources to increase the reliability and accuracy of identifying plant leaf diseases. Fusion approaches combine information from several sources, such as various pictures or feature kinds, to produce a more complete view of the plant leaf and its illness. Constructing a trustworthy and accurate system that can automatically recognise the symptoms of diseases in tomato leaves utilising several sources of data including pictures, spectral reflectance, and environmental parameters is the major objective of tomato leaf disease detection using machine learning. This approach can assist farmers and agricultural professionals in identifying the disease early, stopping it from spreading and acting quickly to reduce crop losses.
References
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