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All Journal Journal of Environmental Engineering and Sustainable Technology Register: Jurnal Ilmiah Teknologi Sistem Informasi
Bihanda, Yusuf Gladiensyah
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy Environmental Science Mechanical Engineering

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Color space and color channel selection on image segmentation of food images Maulana, Luthfi; Bihanda, Yusuf Gladiensyah; Sari, Yuita Arum
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 6, No 2 (2020): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v6i2.2061

Abstract

Image segmentation is a predefined process of image processing to determine a specific object. One of the problems in food recognition and food estimation is the lack of quality of the result of image segmentation. This paper presents a comparative study of different color space and color channel selection in image segmentation of food images. Based on previous research regarding image segmentation used in food leftover estimation, this paper proposed a different approach to selecting color space and color channel based on the score of Intersection Over Union (IOU) and Dice from the whole dataset. The color transformation is required, and five color spaces were used: CIELAB, HSV, YUV, YCbCr, and HLS. The result shows that A in LAB and H in HLS are better to produce segmentation than other color channels, with the Dice score of both is 5 (the highest score). It concludes that this color channel selection is applicable to be embedded in the Automatic Food Leftover Estimation (AFLE) algorithm.
NUTRITION ESTIMATION OF LEFTOVER USING IMPROVED FOOD IMAGE SEGMENTATION AND CONTOUR BASED CALCULATION ALGORITHM Adinugroho, Sigit; Sari, Yuita Arum; Maligan, Jaya Mahar; Sari, Kartika; Bihanda, Yusuf Gladiensyah; Nuraini, Nabila; Fatchurrahman, Danial
Journal of Environmental Engineering and Sustainable Technology Vol 9, No 01 (2022)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jeest.2022.009.01.5

Abstract

In pandemic conditions, awareness of keeping a healthy balance is necessary. One is considering food consumption and understanding its nutrition content to avert food waste. We have been developing a prototype to estimate the nutrition of leftover food, and the main problem lies in image segmentation. Therefore, we propose the Improved Food Image Segmentation (IFIS) and Contour Based Calculation (CBC) to measure the area of the segmented image instead of pixel-wise. First, the tray box image is acquired and broken down into compartments using an automated cropping algorithm. The first step of this proposed method is tray box image acquisition and dividing the compartment using an automatic cropping algorithm. Then each compartment is treated using IFIS, calculates the result of IFIS by CBC, measures the estimated leftover by Automatic Food Leftover Estimation (AFLE), and then predicts the nutritional content. The evaluation is applied by comparing the actual measurement from the Comstock method and leftover estimation by the proposed algorithm. The result shows that Root Square Means Error (RMSE) reaches 0.48 compared to the actual weighing scale and 96.67% accuracy compared to the Comstock method. Based on the results, the proposed algorithm is sufficient to be applied.
Co-Authors Fatchurrahman, Danial Jaya Mahar Maligan Jayawarsa, A.A. Ketut Luthfi Maulana, Luthfi Nuraini, Nabila Sigit Adinugroho Yuita Arum Sari