Computer Vision based Food Recognition with Nutrition Analysis

Computer Vision based Food Recognition with Nutrition Analysis

1 Dr. SHANKARAGOWDA B B , 2 LATHA K B

1 Associate Professor & HOD, Department of Master of Computer Application, BIET, Davangere

2Student, Department of MCA, BIET, Davangere

Abstract- Computer vision based food recognition is a technology  Overall computer vision based food nutrition analysis is  an   application That uses machine learning algorithms to identify an classify different types of food in digital images or videos. This technology has a wide range of applications, including dietary analysis and tracking, nutrition labelling, and food safety. One of the key benefits of food recognition is the ability to automatically extract nutritional information from food images. This can be particularly useful for individuals who are trying to maintain a healthy diet, as it allows them to easily track their daily caloric intake and ensure that they are getting the necessary nutrients. There are several different approaches to food recognition, including using machine learning algorithms to analyse images of food, using pattern recognition techniques to identify specific features of different types of food, and using deep learning techniques to classify images based on their visual characteristics. Overall, computer vision based food recognition has the potential to revolutionize the way we think about food and nutrition, and could have a significant impact on public health.

Keywords – Convolutional Neural Network, Deep Learning, IoU, Machine Learning, R-CNN