A REST API for optical character recognition in food labels
DOI:
https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1316Keywords:
Image Processing, Computer-Assisted, Food Hypersensitivity, Food LabelingAbstract
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.
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