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Agriculture plays a crucial role in feeding the growing population, particularly in Asia where over 70% of the population depends on it. However, crop quality and quantity can be significantly affected by diseases, leading to agricultural losses. Detecting diseases early is essential to prevent such losses. This project aims to develop a software solution that can automatically detect and classify plant diseases. The process involves loading an image, pre-processing it, segmenting it to isolate the relevant parts, extracting features, and finally classifying the disease based on the features. This software can be particularly useful in detecting diseases in plant leaves. The use of image processing techniques in agriculture can help to improve crop yields, prevent losses, and ensure food security.
Keywords:
Plant disease detection using matlab and image processing
Cite Article:
"From Pixels to Pathogens: A MATLAB Based Approach to Plant Disease Identification", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 7, page no.710 - 720, July-2023, Available :http://www.ijrti.org/papers/IJRTI2307102.pdf
Downloads:
000205263
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator