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Classification of fruits into different categories on the basis of their species, quality, size or shape is an aspect which the research community are trying to automate for over a decade. Due to limitations of manual process of segregation of fruits into their required respective class, the development of such smart systems is highly required. In this paper, based color and edge feature, three species of fruits including apples, bananas, and oranges are segregated into their respective classes using machine learning algorithms. For these three types of fruits, for the dataset development, total of 9600 images were acquired. To evaluate the performance of the machine learning based algorithms, five parameters including accuracy, Jaccard score, precision, recall, and F-1 Score are evaluated and compared to determine the best suitable algorithm for classification of fruits. Four machine learning algorithms and the traditional convolutional neural network (CNN) based classification models were used for classification of fruits into their respective classes. From the results it was observed that Decision Tree and Random Forest based models were best suited for classification of fruits with a high accuracy of 98.47% and 98.63% respectively.
Keywords:
Smart Agriculture, Fruit Classification, Machine Learning, Image Processing, Human Computer Interaction
Cite Article:
"Feature Based Fruit Classification using Machine Learning Algorithms: A Comparison ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 3, page no.a452-a459, March-2025, Available :http://www.ijrti.org/papers/IJRTI2503059.pdf
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000446
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator