In this thesis, the problem of developing a mobile application that enables the recognition of additives in products using the camera is addressed. Our approach is based on the use of ML Kit library, which allows image analysis and recognition of additives on product labels. For data storage, we used the Firebase Realtime Database platform, which enables easy storage and updating of additives. The result of this thesis is the development of a functional mobile application that allows users to easily scan products and recognize additives. On average detection accuracy of additives on the products is 70,56%. Our thesis contributes to the development of an efficient solution for additive recognition through a mobile application, providing users with an easy way to obtain additional information about additives in product labels.
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