Banana ripeness classification using computer vision-based mobile application

Mohamedon, Muhammad Farhan and Abd Rahman, Faridah and Mohamad, Sarah Yasmin and Khalifa, Othman Omran (2021) Banana ripeness classification using computer vision-based mobile application. In: 2021 8th International Conference on Computer and Communication Engineering (ICCCE), 22-23 June 2021, Kuala Lumpur, Malaysia.

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Abstract

The integration of smartphone applications with the increasingly growing influence of artificial intelligence provides users with new ways to do about anything and allows users to be practical. In this paper, a mobile application to identify the ripeness of banana fruits is built by implementing a computer vision technique. Image classification is performed by adopting transfer learning to extract edges from a pretrained model. Convolutional neural network (CNN) model is used to train the classifier. Banana is chosen as an instance due to its short shelf life and widely consumed by Malaysian. For this project, Google Colab is utilized for the code execution as it is run on cloud and well-suited for machine learning. TensorFlow Lite with Model Maker library simplified the process of adapting and converting a TensorFlow neuralnetwork model to particular input data before deploying to an Android application. The result emerged with an accuracy of 98.25%. The app can instantly recognize banana live image, display the ripeness level on the screen based on highest percentage matched and display the ripeness, enabling the users to identify the banana ripeness quickly and easily.

Item Type:	Proceeding Paper (Plenary Papers)
Uncontrolled Keywords:	deep learning, computer vision, machine learning, mobile application, banana ripeness classification, convolutional neural networks (CNN), transfer learning
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Engineering
Depositing User:	Dr Sarah Yasmin Mohamad
Date Deposited:	29 Jul 2024 09:41
Last Modified:	29 Jul 2024 09:41
URI:	http://irep.iium.edu.my/id/eprint/113445

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