Fruit Classification and Grading


Authors : Akshay Haridas; Ananthakrishnan K; Adwaitha Shyam; Ann Maria Joy

Volume/Issue : Volume 7 - 2022, Issue 6 - June

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3RfPBiH

DOI : https://doi.org/10.5281/zenodo.6800665

Abstract : This project aims at classifying fruits according to their quality and then grading them according the same. At present we focus on classifying mango taking its outer physical structure into consideration. Mango is a commercial fruit that is grown and enjoyed all over the world.For business purposes, mangoes must be categorised according to their quality. This classification is currently done manually, which is inefficient and prone to human mistake.It also increases personnel, lowering the overall cost and effectiveness of the mango processing sectors. We presented a classification system for mangoes based on changes in their visual characteristics in this research. The methods proposed can be used on any other mango species that changes colour during the ripening phase. Here we use a CNN model for classification. The dataset was acquired from “The Ministry of Education Artificial Intelligence Competition and Annotated Data Collection Project (MOE AI competition and labeled data acquisition project)”. There were three sets of data for training, testing and validation.

This project aims at classifying fruits according to their quality and then grading them according the same. At present we focus on classifying mango taking its outer physical structure into consideration. Mango is a commercial fruit that is grown and enjoyed all over the world.For business purposes, mangoes must be categorised according to their quality. This classification is currently done manually, which is inefficient and prone to human mistake.It also increases personnel, lowering the overall cost and effectiveness of the mango processing sectors. We presented a classification system for mangoes based on changes in their visual characteristics in this research. The methods proposed can be used on any other mango species that changes colour during the ripening phase. Here we use a CNN model for classification. The dataset was acquired from “The Ministry of Education Artificial Intelligence Competition and Annotated Data Collection Project (MOE AI competition and labeled data acquisition project)”. There were three sets of data for training, testing and validation.

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