RECOGNITION AND CLASSIFICATION OF CASSAVA LEAF DISEASES USING MACHINE LEARNING TECHNIQUES

Registration ID: IJNRD_181076

Published ID: IJNRD2204095

DOI: http://doi.one/10.1729/Journal.30119

Nisha P , Dr.J.Vijayakumar

CLAHE, SVM, Plant disease, FUZZY logic

Recently, one of the active research areas in agriculture is the productivity and quality of a crop. Image processing and deep learning techniques are being used to recognize plant diseases, which is a hot research topic right now. The majority of research has focused on identifying illnesses using images of complete leaves. Plants are considered essential because they supply mankind with a source of energy. Between seeding and harvesting, plants can be affected at any time. The plant is affected by several infections like viruses, bacteria, and fungal. If pre-preparing is not followed, it will have serious consequences for the plants, as well as a reduction in product quality, quantity, and productivity. Image processing is an early stage of plant disease detection role-playing the well. The goal of this research work is to develop an image recognition system that can recognize plant diseases. Nowadays we need automatic plant disease detection for increasing the food crops and, easily diagnosis the disease. The cassava plant is a worldwide food crop, and it is the third-largest source of food carbohydrates. The early stage of cassava leaf disease detection is very important in the agriculture field. The cassava leaf images are used for the disease identification process. The hybrid algorithm includes the pre-processing steps and the segmentation process is done using the CLAHE. Then the K-means cluster and GLCM are used for the feature affected area identification. The diseased image is classified by the SVM classifiers. Finally, the disease grade is measured by fuzzy logic. The result, we have achieved are more useful and they prove to the helpful for farmers during the cultivation of cassava, which is a major food crop in the world.

Published Paper   E-Certificate

Nisha P & Dr.J.Vijayakumar (April-2022). RECOGNITION AND CLASSIFICATION OF CASSAVA LEAF DISEASES USING MACHINE LEARNING TECHNIQUES. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(4), 783-791. http://doi.one/10.1729/Journal.30119

Volume 7 Issue 4, April-2022

Pages : 783-791

Paper Reg. ID: IJNRD_181076

Published Paper Id: IJNRD2204095

Downloads: 000121998

Research Area: Science & Technology

Country: Coimbatore, Tamilnadu, India

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Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2204095

Crossref DOI: http://doi.one/10.1729/Journal.30119

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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