Research Article
Automatic Food Labels Reading System
@INPROCEEDINGS{10.1007/978-3-031-60665-6_32, author={Diogo Pires and V\^{\i}tor Filipe and Lio Gon\`{e}alves and Ant\^{o}nio Sousa}, title={Automatic Food Labels Reading System}, proceedings={Wireless Mobile Communication and Healthcare. 12th EAI International Conference, MobiHealth 2023, Vila Real, Portugal, November 29-30, 2023 Proceedings}, proceedings_a={MOBIHEALTH}, year={2024}, month={6}, keywords={Nutri-Score Digital Image Processing Artificial intelligence Deep Learning Image Classification}, doi={10.1007/978-3-031-60665-6_32} }- Diogo Pires
Vítor Filipe
Lio Gonçalves
António Sousa
Year: 2024
Automatic Food Labels Reading System
MOBIHEALTH
Springer
DOI: 10.1007/978-3-031-60665-6_32
Abstract
Growing obesity has been a worldwide issue for several years. This is the outcome of common nutritional disorders which results in obese individuals who are prone to many diseases. Managing diet while simultaneously dealing with the obligations of a working adult can be difficult. Today, people have a very fast-paced life and sometimes neglect food choices. In order to simplify the interpretation of the Nutri-score labeling this paper proposes a method capable of automatically reading food labels with this format. This method is intended to support users when choosing the products to buy based on the letter identification of the label. For this purpose, a dataset was created, and a prototype mobile application was developed using a deep learning network to recognize the Nutri-score information. Although the final solution is still in progress, the reading module, which includes the proposed method, achieved an encouraging and promising accuracy (above 90%). The upcoming developments of the model include information to the user about the nutritional value of the analyzed product combining it’s Nutri-score label and composition.
