Ingredients Identification Through Label Scanning Using PaddleOCR and ChatGPT for Information Retrieval - Rosyadi, Ahmad Wahyu; Siti Ma’shumah; Muhammad Qomaruz Zaman; Moh. Rizki Fajar (Ikatan Ahli Informatika Indonesia (IAII), 2024)
Human health depends on choosing food ingredients that align with dietary needs and avoid allergens. However, consumers often encounter unfamiliar ingredients that require additional information. Traditionally, they search online by typing in the ingredient's name which can be time-consuming and may not yield relevant results. Therefore, a system to identify and display ingredient information is necessary. This study proposes a new system that identifies ingredients by scanning the composition label on packaging using PaddleOCR and retrieving information through ChatGPT on a smartphone. The process begins with capturing an image of the composition label. Then PaddleOCR is employed to extract text from the scanned label, enabling identification of the listed ingredients. Subsequently, ChatGPT retrieves detailed information about the desired ingredients and displays it, allowing users to easily understand the ingredients. The system's effectiveness in text recognition is assessed using the character error rate (CER). The results show robust performance by achieving an average CER of 0.14, with flat packaging reaching an impressive CER of 0.05. Additionally, the system's usability was assessed through pilot testing which received significant positive user feedback achieving 4.37 satisfaction level on Likert scale, particularly regarding the clarity and relevance of the ingredient information provided.