Scopus Indexed Paper

Paper Details


Title
Computer vision based local fruit recognition
Abstract
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 capturedimage 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
Keywords
Computer vision, Feature extraction, Image segmentation, Local fruit, Performance metrics, Support vector machine(SVM)
Authors
Md. Robel Mia, Md. Jueal Mia, Anup Majumder, Soummo Supriya, Md. Tarek Habib
Phone
Journal or Conference Name
International Journal of Engineering and Advanced Technology
Publish Year
2019
Indexing
Scopus