A Specific Marker Approach to Improve Object Recognition in Bullet Launchers with Computer Vision

Umar Ali Ahmad; Wildan Panji  Tresna; Iyon Titok  Sugiarto; Mera Kartika  Delimayanti; Fahmi Charish Mustofa; Mohammad Reza Faisal; Reza Rendian  Septiawan

doi:10.35882/jeeemi.v6i4.460

Umar Ali Ahmad Kanazawa University
Wildan Panji Tresna National Research and Innovation Agency
Iyon Titok Sugiarto National Research and Innovation Agency
Mera Kartika Delimayanti Politeknik Negeri Jakarta
Fahmi Charish Mustofa National Land Agency
Mohammad Reza Faisal Lambung Mangkurat University
Reza Rendian Septiawan Telkom University

DOI: https://doi.org/10.35882/jeeemi.v6i4.460

Keywords: Computer Vision, Object Recognition, Markers, Duty Cycle

Abstract

Computer vision’s ability determines the accuracy of object recognition. This study tested the camera's ability to recognize both passive and active markers using LEDs. A specific active marker is analyzed using blinking on the LED. One of the factors to consider when choosing a specific marker is the value of the duty cycle accuracy. The proposed system is confirmed by implementing an integrated control system and the hardware to develop a specific marker. The result shows that the commercial camera can recognize all colors used as the test markers. Here, a specific marker was improved in the bullet launcher system due to tracking, identifying, detecting, marking, locking, and shooting a target precisely. Generally, image processing obtained the comparison of the time to speed the process, the higher the pixel resolution, the longer the time. When the object moves at a certain speed, the camera can detect several marker shapes, such as circles, squares, and triangles. The result shows that a circle marker gives a higher accuracy at every speed level. In the duty cycle variation test, when the duty cycle value is set to 50%, the best accuracy is obtained when the red LED is used, with the accuracy value obtained reaching 96%. In the LED test, it is also found that the effect of light affects the color detection results on the LED. Moreover, using the highest accuracy results from the LEDs at the implementation stage would be very good.

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