Literature Survey—Food Recognition and Calorie Measurement Using Image Processing and Machine Learning Techniques

One of the most difficult aspects of obesity therapy is determining how much food obese individuals consume on a daily basis. A computer vision-based approach is used in this study to estimate calorie consumption from food photographs. Propose a Food Recognition System (FRS) for the calculation of calories and nutrient values. The system next analyses and categorises the photos to determine the type of food and portion size, and then uses that information to calculate the calories in the food. In today's food identification applications, emerging food categorization methods are critical. A new food recognition algorithm is provided for this purpose, taking into account the shape, colour, size, and texture features of the item. A better classification will be attained by using various combinations of these features. Dietitians can use this food calorie and nutrition assessment method to track and control their daily food intake. The texture, shape, and size properties of the food image are then retrieved using the CNN. The better the classification, the more accurately the calories of the food may be estimated..

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Food Region Extraction Based on Saliency Detection Model

Kitada

Futagami

Hayasaka

2021

Transactions of ISCIE

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In this paper, we propose a method that can automatically extract food regions from food images by using the saliency detection model based on a deep neural network (DNN) and the saliency thresholding method based on the average saliency value. Our experiment, using 125 food images from a food recording tool on smartphone applications, demonstrates that the proposed method significantly increased average F-measure by 4.22% or more compared with both the conventional method using local extrema and food extraction using DNN trained with 1017 food images. Our proposed method also increased average precision and recall by 0.13% or more and 11.38% or more, respectively. We also discussed the effectiveness and the future development of food extraction using the saliency detection model and saliency thresholding method on the basis of experimental results.

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Literature Survey—Food Recognition and Calorie Measurement Using Image Processing and Machine Learning Techniques

Cited by 3 publications

References 23 publications

Improvement of Food Region Extraction based on Prior Knowledge and Comparative Evaluation using Actual Images

Improvement of Food Region Extraction based on Prior Knowledge and Comparative Evaluation using Actual Images

Food Calories Estimation Using Image Processing

Food Region Extraction Based on Saliency Detection Model

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