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All Journal Journal of Information Technology and Computer Science
Hurriyatul Fitriyah
University of Brawijaya
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Automatic Measurement of Human Body Temperature on Thermal Image Using Knowledge-Based Criteria Hurriyatul Fitriyah; Aditya Rachmadi; Gembong Edhi Setyawan
Journal of Information Technology and Computer Science Vol. 2 No. 2: November 2017
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (189.494 KB) | DOI: 10.25126/jitecs.20172235

Abstract

Instead of thermometer, an infrared camera could be uti-lized to scan body temperature instantly and non-contact. This paperproposed a non-contact measurement of human body temperature by au-tomatically locating inner-chantus on thermal images. The inner-canthuswere detected in both eyes individually. It located inner-canthi based ontemperature where inner-canthi has the highest temperature in face area.A Thresholding based on 9-highest temperature were applied to detectcandidates of inner-canthus' blob as it must have minimum 9 pixel areaaccording to the Standard. Three knowledge based on characteristic ofeye were also applied in the algorithm as several spot in face usuallyfalls within the temperature threshold. The result show accuracy of al-gorithm to detect eye is 82% whether the eyelids were open or closed.There is no signicant dierent of temperature between closed and openeyes based on paired t-test. The algorithm also showed similar result tothermometer measurement based on paired t-test.
Applying Linear Regression to Estimate Weight of Non Axi-Symmetric fruit Hurriyatul Fitriyah; Eko Setiawan; Muhammad Rifqi Radifan Masruri
Journal of Information Technology and Computer Science Vol. 5 No. 2: August 2020
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1259.483 KB) | DOI: 10.25126/jitecs.202052163

Abstract

Weight is an important parameter in fruits’ quality identification. Measuring fruits’ weight using scale is tedious since fruits must be taken from tree and placed on contact to scale. Many researches have proposed non-contact estimation methods of fruits’ weight using 2D images. The studies were commonly applied in axi-symmetric fruits, such oranges. In this paper, an algorithm to estimate weight of non axi-symmetric fruit is developed. It used a Linear Regression rather than geometric-based methods as proposed by other researches. The non axi-symmetric fruits chosen was star fruits. It is a challenging fruits since its basic shape is not round but irregular star shape. The estimation used pixel count from one-view image of the fruits’ projection as feature. The proposed method has RMSE of 16.322 Gram and MAPE of 7.089% compare to the expected weights. It also has high Coefficient of Determination, R^2, 0.8829 compare to the weight scale measurement.
Co-Authors Aditya Rachmadi Eko Setiawan Gembong Edhi Setyawan Muhammad Rifqi Radifan Masruri