The Design and Implementation of an Ingredient-Based Food Calorie Estimation System Using Nutrition Knowledge and Fusion of Brightness and Heat Information

Abstract

To measure the calorie of food, which are varied depending on its ingredients and volume in each cooking time, it is required to calculate calories of food before consuming. Based on nutrition knowledge, ingredients that are components of food naturally have different calories. This paper proposes a method of ingredient-based food calorie estimation using nutrition knowledge and thermal information. In this method, an image of the food is first recognized as a type of food, and ingredients of the recognized food are retrieved from the database with their nutrition knowledge and pattern of brightness and thermal images. Simultaneously, the image is segmented into boundaries of ingredient candidates, and all boundaries are then classified into ingredients using fuzzy logic based on their heat pattern and intensities. The classified ingredients from all boundaries are finally calculated for total calories based on area ratio and nutrition knowledge. The performance of our proposed method shows acceptable results comparing with the calories set up by the conventional destructive method.

Keywords

• Food calorie
• ingredient-based
• nutrition knowledge
• fuzzy model
• food-calorie estimation
• classification