Smartphone Based Food Classification: Applications, Challenges, and Future Prospects for Diabetics

Diabetes has become a global health concern, posing risk to millions of individuals. Managing dietary consumption is crucial for the overall health of diabetic patients. Traditional methods of monitoring food intake can be tedious and unreliable. However, computer vision-based solutions, such as image-based food recognition systems (FIRS) using mobile cameras, offer automated and efficient ways to track food intake. This systematic review examines mobile computer vision approaches for food classification, volume estimation, and calorific measurement. Besides, the study discusses the potential integration of Glycemic Index estimation to FIRS to benefit diabetic patients. Future directions and issues related to FIRS are also explored.