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Type :article
Subject :QM Human anatomy
ISSN :1742-6588
Main Author :Khairudin, Moh
Additional Authors :Arman Shah Abdullah
Title :Object detection robot using fuzzy logic controller through image processing
Place of Production :Tanjung Malim
Publisher :Fakulti Teknikal Dan Vokasional
Year of Publication :2021
Notes :Journal of Physics: Conference Series
Corporate Name :Universiti Pendidikan Sultan Idris
Web Link :Click to view web link
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Abstract : Universiti Pendidikan Sultan Idris
This study presents a robot movement in tracking 2D objects. This input image is transformed into another image by certain techniques. In this study, by utilizing image processing, the robot can work to detect objects in the form of hexagons. Apart from detecting the detected shape, this image processing is also for detecting color. So that a hexagon-shaped 2D object will be detected with the magenta color that has been set in advance. The movement of this robot is to follow the motion of objects horizontally. While the object is shifted to the right, the robot will move to the right, and if the object is shifted to the left, the robot will move to the left. Robot movement is controlled by fuzzy logic. There are 5 membership functions to divide the object's position area and 5 membership functions output to adjust the speed and direction of the robot's motion. ? 2021 Published under licence by IOP Publishing Ltd.


Alawad, A. M., Rahman, F. D. A., Khalifa, O. O., & Malek, N. A. (2018). Fuzzy logic based edge detection method for image processing. International Journal of Electrical and Computer Engineering, 8(3), 1863-1869. doi:10.11591/ijece.v8i3.pp1863-1869

Amza, C. G., & Cicic, D. T. (2015). Industrial image processing using fuzzy-logic. Paper presented at the Energy Procedia, , 100(C) 492-498. doi:10.1016/j.proeng.2015.01.404 Retrieved from

Andre, M., Tiago, M., Szymon, L., & Rita, A. (2017). Land Cover Classification from Multispectral Data using Computational Intelligence Tools: A Comparative Study Information, 8 Retrieved from

Andrea, K., Andres, G., Eyberth, R., & Carlos, S. (2013). Edge detection algorithm based on fuzzy logic theory for a local vision system of robocup humanoid league tecno. Lógicas, 30, 33-50. Retrieved from

Athanasiadis, E. I., Cavouras, D. A., Spyridonos, P. P., Glotsos, D. T., Kalatzis, I. K., & Nikiforidis, G. C. (2009). Complementary DNA microarray image processing based on the fuzzy gaussian mixture model. IEEE Transactions on Information Technology in Biomedicine, 13(4), 419-425. doi:10.1109/TITB.2008.907984

Bai, Y., & Zhuang, H. (2007). Fuzzy Logic for Image Processing: Definition and Applications of a Fuzzy Image Processing Scheme, Retrieved from

Changick, K., & Jenq, N. (2002). Fast and automatic video object segmentation and tracking for content-based applications. IEEE Transactions on Circuits and Systems for Video Technology, , 12. Retrieved from

Haq, I., Anwar, S., Shah, K., Khan, M. T., & Shah, S. A. (2015). Fuzzy logic based edge detection in smooth and noisy clinical images. PLoS ONE, 10(9) doi:10.1371/journal.pone.0138712

Ismail, M. E., Masran, S. H., Rahim, M. B., Faizal, A. N., & Marian, M. F. (2017). Development of electrical discharge machine die sinking application using android platform. Jurnal Pendidikan Teknologi Dan Kejuruan, 23(4), 339-345. Retrieved from

Khairudin, M., Chen, G. D., Wu, M. C., Asnawi, R., & Nurkhamid. (2019). Control of a movable robot head using vision-based object tracking. International Journal of Electrical and Computer Engineering, 9(4), 2503-2512. doi:10.11591/ijece.v9i4.pp2503-2512

Khairudin, M., Refalda, R., Yatmono, S., Pramono, H. S., Triatmaja, A. K., & Shah, A. (2020). The mobile robot control in obstacle avoidance using fuzzy logic controller. Indonesian Journal of Science and Technology, 5(3), 334-351. doi:10.17509/ijost.v5i3.24889

Khan, A., Li, J. -., & Shaikh, R. A. (2016). Medical image processing using fuzzy logic. Paper presented at the 2015 12th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2015, 163-167. doi:10.1109/ICCWAMTIP.2015.7493967 Retrieved from

Melin, P., Gonzalez, C. I., Castro, J. R., Mendoza, O., & Castillo, O. (2014). Edge-detection method for image processing based on generalized type-2 fuzzy logic. IEEE Transactions on Fuzzy Systems, 22(6), 1515-1525. doi:10.1109/TFUZZ.2013.2297159

Schröder, T., Krüger, K., & Kümmerlen, F. (2014). Image processing based deflagration detection using fuzzy logic classification. Fire Safety Journal, 65, 1-10. doi:10.1016/j.firesaf.2014.02.004

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