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Analysis of Classification Algorithms for Plant Leaf Disease Detection

Publication Type : Conference Paper

Publisher : IEEE

Source : 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), IEEE, Coimbatore, India (2019)

Url : https://ieeexplore.ieee.org/document/8869090

Campus : Amritapuri

School : School of Engineering

Department : Electronics and Communication

Year : 2019

Abstract : Agribusiness is the essential occupation in India, that assumes a vital job in the economy of the nation. Yearly 15.7 percentage of the crops are being lost due to attack by insect pests and diseases [1]. The diseases caused will lead to a reduction of quality and quantity of crops. To maintain the health of the plant, it is required to identify the infection and give reasonable consideration. It is difficult to do physically because the human eye cannot observe the minute variations of the infected part of the leaf. In this way, we have built up a framework programming utilizing Matlab [2] to distinguish plant leaf illnesses by utilizing picture handling procedures. The software is produced so that a man even who don't have earlier learning about the plants, and their ailments can effectively recognize infected leaves. We have utilized k-means clustering to distinguish the tainted region of the plant leaf. The diseased recognition part incorporates picture obtaining, image pre-processing, segmentation and feature extraction and SVM classification.

Cite this Research Publication : J. N. Reddy, Vinod, K., and Remya Ajai A. S., “Analysis of Classification Algorithms for Plant Leaf Disease Detection”, in 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), Coimbatore, India, 2019.

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