A Novel RGB-Depth Imaging Technique for Food Volume Estimation - Sari, Yuita Arum (Prodi Sistem Informasi Universitas Dharma Andalas, 2025)
Evaluating nutrient intake among patients in a hospital is crucial, as it can accelerate their recovery process. Estimating calorie intake can be achieved by monitoring the quantity of food consumed by patients both before and after their meals. This approach involves various methods, including the use of digital scales, the Comstock level, and digital imaging techniques. Nonetheless, these techniques have their own limitations, particularly the risk of subjective assessments. To reduce errors arising from human factors, an objective evaluation is proposed. This paper introduces a new technique for measuring volume using RGB-Depth images. The method incorporates image segmentation and edge detection in RGB images to correspond with the depth image. Subsequently, the segmented regions and boundaries from the depth images are converted into point clouds. The volume of interest is calculated by fitting the point cloud to an ellipsoid. The lowest Mean Average Percentage Error (MAPE) is 2.73. It indicates that the proposed method is sufficient to measure the food volume.