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Hierarchical approach for ripeness grading of mangoes

Artificial Intelligence in Agriculture 2020年第1期4卷 243-252页

作者： Anitha Raghavendra D.S.Guru Mahesh K.Rao R.Sumithra Maharaja Institute of Technology Mysore BelawadiS.R.Patna TalukMandya 571477India Department of Studies in Computer Science ManasagangothriUniversity of MysoreMysore 570006India

Grading of fruits based on their ripeness has been a topic of research for the last two *** the ripened mangoes has become more of an art than science and is a challenging *** study aims at introducing a system to grademangoes with four classes based on their *** study was demonstrated through an extensive experimentation on a newly created dataset consisting of 981 images of alphonsomango variety belonging to four classes viz.,under-ripen,perfectly ripen,over-ripen with internal defects and over-ripen without internal *** this study,a hierarchical approach was adopted to classify the mangoes into the four *** each stage of classification,L*a*b color space features were *** the purpose of classification at each stage,a number of classifiers and their possible combinationswere tried *** study revealed that,the Support VectorMachine(SVM)classifier works better for classifyingmangoes into under-ripen,perfectly ripen and overripen while the thresholding classifier has a superior classification performance on over-ripen with internal defects and over-ripen without internal ***,to bring out the superiority of the hierarchical approach,a conventional single shot multi-class classification approach with SVMwas also *** results of the experimentation demonstrated that the hierarchical method with an accuracy of 88%outperforms the counterpart conventional single shot multi-class classification approach in addition to several existing contemporary models.

关键词： alphonso mango L*a*b color space Threshold based classifier Support vector machine

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