Recognition and Classification of Pomegranate Leaves Diseases by Image Processing and Machine Learning Techniques

作     者：Mangena Venu Madhavan Dang Ngoc Hoang Thanh Aditya Khamparia Sagar Pande RahulMalik Deepak Gupta 

作者机构：School of Computer Science EngineeringLovely Professional UniversityPunjab144411India University of Economics Ho Chi Minh CityHo Chi Minh City70000Vietnam Maharaja Agrasen Institute of Technology110086India 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2021年第66卷第3期

页      面：2939-2955页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Image enhancement image segmentation image processing for agriculture K-means multi-class support vector machine 

摘      要：Disease recognition in plants is one of the essential problems in agricultural image *** article focuses on designing a framework that can recognize and classify diseases on pomegranate plants *** framework utilizes image processing techniques such as image acquisition,image resizing,image enhancement,image segmentation,ROI extraction(region of interest),and feature *** image dataset related to pomegranate leaf disease is utilized to implement the framework,divided into a training set and a test *** the implementation process,techniques such as image enhancement and image segmentation are primarily used for identifying ROI and *** image classification will then be implemented by combining a supervised learning model with a support vector *** proposed framework is developed based on MATLAB with a graphical user *** to the experimental results,the proposed framework can achieve 98.39%accuracy for classifying diseased and healthy ***,the framework can achieve an accuracy of 98.07%for classifying diseases on pomegranate leaves.