BibTex Citation Data :
@article{JPA27483, author = {Iyon Titok Sugiarto and Jasmine Aulia and Zahra Radila and Zaenal Afif Azhari and Wildan Panji Tresna}, title = {Characteristics of Blue, Red, and Green Lasers for an Object Recognition System as Unique Markers}, journal = {Journal of Physics and Its Applications}, volume = {7}, number = {4}, year = {2025}, keywords = {Computer Vision; Image Processing; Object Recognition System; Unique Marker; Laser Blinking}, abstract = { Computer Vision (CV) is an automation technology with applications in national defense, particularly for enabling automated object targeting systems. This study focuses on developing a unique marker detection system to support such targeting capabilities. The markers consist of laser beams characterized by distinct colors, shapes, sizes, and blinking patterns, designed to be identifiable only by a programmed computer system. Incorporating these laser properties as input parameters is essential for effective object recognition. Experimental results indicate that the detection threshold was calibrated to identify red, green, and blue colored objects under indoor lighting conditions of 71.3 Lux. The CV system successfully identified a circular marker positioned 680 cm away from triangular and square markers. In distance estimation tests using a Logitech C615 HD camera, the system achieved average error rates of 4% for circles, 5% for rectangles, and 6% for triangles. Overall, the system demonstrated a tracking accuracy of 95.24% for unique markers placed at distances ranging from 50 to 300 cm. }, issn = {2622-5956}, pages = {162--167} doi = {10.14710/jpa.v7i4.27483}, url = {https://ejournal2.undip.ac.id/index.php/jpa/article/view/27483} }
Refworks Citation Data :
Computer Vision (CV) is an automation technology with applications in national defense, particularly for enabling automated object targeting systems. This study focuses on developing a unique marker detection system to support such targeting capabilities. The markers consist of laser beams characterized by distinct colors, shapes, sizes, and blinking patterns, designed to be identifiable only by a programmed computer system. Incorporating these laser properties as input parameters is essential for effective object recognition. Experimental results indicate that the detection threshold was calibrated to identify red, green, and blue colored objects under indoor lighting conditions of 71.3 Lux. The CV system successfully identified a circular marker positioned 680 cm away from triangular and square markers. In distance estimation tests using a Logitech C615 HD camera, the system achieved average error rates of 4% for circles, 5% for rectangles, and 6% for triangles. Overall, the system demonstrated a tracking accuracy of 95.24% for unique markers placed at distances ranging from 50 to 300 cm.
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