Food Recognition and Calorie Measurement Using Ai

Author Name

Rahul S, Latha Sivasankari

ABSTRACT:

         With the rapid growth of artificial intelligence in healthcare and lifestyle management, automated dietary monitoring systems are becoming increasingly important. This project presents an intelligent food recognition and calorie measurement system using AI techniques. The system uses image processing and deep learning models to identify food items from images captured by a user through a mobile device or camera.

A convolutional neural network (CNN) model is trained on a large dataset of food images to accurately classify different food categories. Once the food item is recognized, the system estimates its nutritional information, particularly calorie content, by referencing a pre-built food nutrition database.

The proposed system aims to help users track their daily calorie intake automatically without manual logging, making diet monitoring more convenient and accurate. Such a system can support individuals who want to maintain a healthy lifestyle, manage weight, or monitor medical conditions like obesity and diabetes.

Overall, this AI-based solution demonstrates how computer vision and machine learning can simplify dietary tracking and promote healthier eating habits.

features from images. In a food recognition system, the CNN modelprocesses the captured food image and predicts the type