Dietary Supplement Products Registration Verification Application Using Thai FDA Number Images with OpenAI Vision API

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Authors: Arnon Phongrusamepane, Nattapat Thongkaew, Teetach Chuenkamonrat, Chalothon Chootong, Chatchai Kasemtaweechok
Cited by: 1
References: 26

Abstract

Thai Food and Drug Administration (FDA) registration numbers displayed on product labels are essential for verifying the authenticity of dietary supplements. This study aims to develop a Dietary Supplement Verification Application (DSVAPP) that enables consumers to upload images of product labels containing FDA registration numbers to authenticate products. The system uses the OpenAI vision Application Programming Interface (API) to extract registration numbers, thereby reducing error propagation between object detection and Optical Character Recognition (OCR). DSVAPP is evaluated using 118 images and nine combinations of object detection and OCR methods. The results demonstrate that the DSVAPP incorporating the GPT-5.2 vision model achieves superior performance compared to most evaluated methods.

Fields of Study & Subjects

Image Retrieval and Classification Techniques Nutritional Studies and Diet Handwritten Text Recognition Techniques

Publication details

Journal / source
Proceedings of Engineering and Technology Innovation
Publisher
Taiwan Association of Engineering and Technology Innovation
Volume
33
Pages
51–66
Publication date
8 May 2026
Language
EN