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International Journal of Computer Techniques

ISSN 2394-2231

DOI Registered

Volume 12, Issue 6 | Published: November – December 2025

Author

Bhavannarayan.Ch, Revathi.D , Satya Pratap.G

Abstract

Obesity is a pressing global public health concern closely associated with excess calorie consumption. This project focuses on enhancing food calorie intake estimation and body mass index (BMI) prediction, addressing the limitations of traditional unreliable self-reported methods. By leveraging advancements in computer vision and machine learning, the project aims to create a system that accurately estimates calorie content from food images and predicts BMI using demographic data. A convolutional neural network (CNN) will be trained on a dataset of food images, while a regression model will integrate user demographics for BMI predictions. The methods’ accuracy will be assessed using metrics like mean absolute error and root mean square error, showcasing their feasibility for applications in nutrition and healthcare.

Keywords

Food calorie, BMI, CNN, Machine learning.

Conclusion

This initiative provides an estimation of the calorie content in food and forecasts BMI utilizing Machine Learning and Deep Learning techniques. Through our initial testing of a dataset containing food images analyzed with Mask R-CNN, we can conclude that creating an application to estimate calories from food images is indeed feasible. Such an application is likely to significantly influence people’s views on their meals while also affecting the weight-loss and weight-management sectors. Given that images are captured using smartphones and the image processing techniques applied are mature, integrating this proposed solution into health applications is quite straightforward. Furthermore, we have successfully developed a system capable of predicting BMI from a limited set of participant images. This method could evolve into a public health assessment tool designed to support health initiatives in regions facing widespread obesity or malnutrition. Additionally, the incorporation of silhouettes in our methodology enhances user privacy.

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How to Cite This Paper

Dr.Ch.Bhavannarayana, Dr.D.Revathi, Dr.G.Satya pratap (2025). AI-Powered Nutrition: The Future of Food Calorie Tracking & Obesity Prevention. International Journal of Computer Techniques, 12(6). ISSN: 2394-2231.