Calorie Detection of Food Image based on SVM Algorithm

Abstract

Nowadays, standard intake of healthy food is vital for keeping a diet to avoid obesity within the human body . In this paper, we present a totally unique system supported machine learning that automatically performs accurate classification of food images and estimates food attributes. This paper proposes a machine learning model consisting of a support vector machine that classifies food into specific categories within the training a part of the prototype system. The most purpose of the proposed method is to reinforce the accuracy of the pre-training model. The paper designs a prototype system supported the client server network model. The client sends an image detection request and processes it on the server side. The prototype system is meant with three main software components, including a pre-trained support vector machine training module for classification purposes, a text data training module for attribute estimation models, and a server-side module. We experimented with a selection of food categories, each containing thousands of images, and therefore the machine learning training to understand higher classification accuracy.