A Survey on Food Image Classification and Calorie Prediction Using Machine Learning

Abstract: This work aims to find new techniques for food type recognition, diabetes disease prediction and food recommendation have been proposed for managing the diabetic disease and for recommending food with required calorie for the persons detected with diabetes. Therefore, this Project work focuses on effective methods for identifying the food type and estimating its calorie values with reference to the calorie table. Moreover, it focuses on prediction of diabetic disease. Based on the predicted level of diabetes, food recommendations have been made for the required calorie values. By combining image classification with calorie prediction, the approach aims to empower users in making informed dietary choices and managing their caloric intake more effectively. The proposed method demonstrates promising outcomes in both food item classification accuracy and calorie estimation precision. Its potential application extends to supporting healthier eating habits and aiding dietary monitoring for individuals, dietitians, and the food industry. This technological approach could serve as a valuable tool in promoting nutritional awareness and combating diet-related health issues.