Development of an expert system based on image processing and optical character recognition (OCR)techniques using packaged food product labels

Food labels play a critical role in terms of health, safety, and legal compliance for consumers, businesses, and governments. While providing essential information about product content to consumers, labels also assist businesses in marketing their products and complying with regulatory requirements. Reading labels guides consumers in making informed food choices and lifestyle decisions, potentially improving health indicators. However, label readability may vary depending on consumers' gender, age, marital status, education level, and health condition. Factors such as font size, color tone, and complexity of information presentation can hinder effective label reading, limiting consumer access to information. With the use of expert systems, it is possible to analyze these labels more effectively and make them more understandable with the help of technologies such as optical character recognition. These developments can support consumers in making healthy choices, contributing positively to public health. In this thesis, an expert system capable of reading product label images, understanding label text, and providing recommendations based on Image Processing Techniques and Optical Character Recognition System techniques has been developed. 2024, Haziran + 80 Pages Keywords: Label, Healty Food Choice, Nutrition, Optical Character Recognition, Images Processing Techniques, Expert System