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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 12, 2021.
Abstract: In this paper a new approach of unique markers to detect and track moving objects with the encoding LED marker is presented. In addition, an LED spotlight system that can shoot light in the direction of the target is also proposed. The encoding process is done by making a unique blinking pattern on the LED, and thus the camera and a servomotor as an object recognition system would only recognize a unique marker given by an LED. In this work the camera with OpenCV could capture a unique marker in all variant of blinking patterns. A unique marker is important on object recognition system so the camera could identify the object marked by our unique marker and ignore all other markers that might captured by the camera. In addition, analysis of the PWM signal from an LED is carried out here to determine the characteristics of the LEDs in each color, determine the accuracy of the duty cycle, and the use of the bright-dim method on the LEDs. The results show that the highest accuracy is obtained when a 50% duty cycle is used with the on and off time are set to be 1 second for all LED colors. The benefit of the proposed system is confirmed by implementing an integrated control system as a unique marker. The effectiveness of the blinking LED against other laser interferences is also discussed.
Wildan Pandji Tresna, Umar Ali Ahmad, Isnaeni, Reza Rendian Septiawan, Iyon Titok Sugiarto and Alex Lukmanto Suherman, “Encoding LED for Unique Markers on Object Recognition System” International Journal of Advanced Computer Science and Applications(IJACSA), 12(12), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0121284
@article{Tresna2021,
title = {Encoding LED for Unique Markers on Object Recognition System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0121284},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0121284},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {12},
author = {Wildan Pandji Tresna and Umar Ali Ahmad and Isnaeni and Reza Rendian Septiawan and Iyon Titok Sugiarto and Alex Lukmanto Suherman}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.