Computer Vision Based Local Fruit Recognition

dc.contributor.authorMia, Md. Robel
dc.contributor.authorMia, Md. Jueal
dc.contributor.authorMajumder, Anup
dc.contributor.authorSupriya, Soummo
dc.contributor.authorHabib, Md. Tarek
dc.date.accessioned2022-01-26T10:09:55Z
dc.date.available2022-01-26T10:09:55Z
dc.date.issued2019-10
dc.description.abstractAbstract: Bangladesh is an agricultural country having a tropical monsoon climate. A large variety of tropical and sub-tropical fruits abound in Bangladesh. People of Bangladesh are fruit-lovers too. Currently, most of the people of this country are failing to recognize many of the rare local fruits and the number of this portion of people is increasing day by day. Thus, not only the natural heritage but also good sources of food are being diminished. Performing a machine vision based recognition of these fruits can help people recognize them. In this paper, we perform an in-depth exploration of a computer vision approach for recognizing rare local fruits of Bangladesh. A number of rare local fruits are classified based on the features extracted from their images. For our experiment, we have used a total of 480 images of 6 rare local fruits. We perform some preprocessing on the captured image and then expected features are extracted using image segmentation. Classification of the fruits is accomplished using support vector machines (SVMs). We have achieved 94.79% classification accuracy, which is not only good but also promising for future research.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6895
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6895
dc.language.isoen_US
dc.publisherInternational Journal of Engineering and Advanced Technology
dc.sourceDIU Institutional Repository
dc.subjectComputer vision
dc.subjectFeature extraction
dc.subjectImage segmentation
dc.subjectLocal fruit
dc.subjectPerformance metrics
dc.subjectSupport vector machine (SVM)
dc.titleComputer Vision Based Local Fruit Recognition
dc.typeArticle

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