Food Item Calorie Estimation Using YOLOv4 and Image Processing
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© 2021 by IJCTT Journal
Volume-69 Issue-5
Year of Publication : 2021
Authors : Samidha Patil, Shivani Patil, Vaishnavi Kale, Mohan Bonde
DOI :  10.14445/22312803/IJCTT-V69I5P110

How to Cite?

Samidha Patil, Shivani Patil, Vaishnavi Kale, Mohan Bonde, "Food Item Calorie Estimation Using YOLOv4 and Image Processing," International Journal of Computer Trends and Technology, vol. 69, no. 5, pp. 69-76, 2021. Crossref, https://doi.org/10.14445/22312803/IJCTT-V69I5P110

Abstract
In last decade or two, an increase in growth of obesity has been seen all around the world. There has been increasing research to tackle obesity using food logging and food item calorie analysis. An increase in healthy living has led to numerous food management applications, which have image recognition to automatically record meals. To achieve healthy living it`s important for someone to observe his/her daily calorie intake. The project aims to incorporate modern technique for object detection together with image analysis techniques to determine a more accurate calorie count from images of food items. The strategy employed involves determining the calorie count of the food item through mathematical calculations of the features extracted from food image by image segmentation. In this paper, we propose a mobile software for food calorie estimation from images of food items. By using YOLO- You Only Look Once for Object detection and Image segmentation for calorie estimation we are able to detect the food and thereby calculate the required food calories from the varied datasets of Indian cuisine.

Keywords
Calorie Estimation, Object Detection, YOLO.

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