A REST API for optical character recognition in food labels

Authors

  • Gabriel Menin UFCSPA
  • Renan Augusto Pereira UFCSPA
  • Flávia Magalhães Guedes UFCSPA
  • Ana Trindade Winck UFCSPA

DOI:

https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1316

Keywords:

Image Processing, Computer-Assisted, Food Hypersensitivity, Food Labeling

Abstract

Objective: The global prevalence of food allergies is a public health threat, particularly when allergens are inadvertently consumed. This study aims to develop an Application Programming Interface to extract ingredients information from food labels, which, when integrated into an application, can identify allergens and notify users, enabling them to make informed dietary choices. Method: This work applies an optical character recognition library, calibrated for reading and translating texts from food labels. Results: We performed tests with 76 labeled food products, divided into 7 types of materials, evaluating the similarity between actual labels and the transcriptions, achieving an average similarity rate of 81.61%. Conclusion: The solution proves viable for integration with an allergen recognition application, although the automatic transcription of labels is more favorable for certain types of materials and shapes of food packaging, requiring better calibration for others.

Author Biographies

Gabriel Menin, UFCSPA

Bel, Federal University of Health Sciences of Porto Alegre - UFCSPA, Porto Alegre (RS), Brazil.

Renan Augusto Pereira, UFCSPA

Me, Federal University of Health Sciences of Porto Alegre - UFCSPA, Porto Alegre (RS), Brazil.

Flávia Magalhães Guedes, UFCSPA

Me, Federal University of Health Sciences of Porto Alegre - UFCSPA, Porto Alegre (RS), Brazil.

Ana Trindade Winck, UFCSPA

Dra, Federal University of Health Sciences of Porto Alegre - UFCSPA, Porto Alegre (RS), Brazil.

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Published

2024-11-19

How to Cite

Menin, G., Pereira, R. A., Guedes, F. M., & Winck, A. T. (2024). A REST API for optical character recognition in food labels. Journal of Health Informatics, 16(Especial). https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1316

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