Abstract
This article proposes methods for maximising the detection rates of thermal fiducial markers using thermography. By exploring the combination of image processing techniques with the use of an affordable thermographic camera, the aim is to mitigate the negative effects of thermography and improve accurate marker identification in a variety of mounting and distance conditions. The research identified a diversity of processing techniques capable of improving thermal marker recognition, offering the potential to surpass previous results. The results highlight the possibility of using low-cost thermographic cameras for this purpose, which could democratise and reduce the costs of recognition processes. This methodology validates the proposed approach, providing a robust basis for future improvements in thermal marker detection and promoting the feasibility of practical, low-cost applications in an assortment of fields.
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Notes
- 1.
Results were obtained both with and without the application of the steps, to evaluate the effectiveness of the transformations.
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Acknowledgments
The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI, UIDB/05757/2020 (DOI: 10.54499/UIDB/05757/2020) and UIDP/05757/2020 (DOI: 10.54499/UIDP/05757/2020) and SusTEC, LA/P/000 7/2020 (DOI: 10.54499/LA/P/0007/2020).
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França, A., Berger, G.S., Mendes, A., Lima, J. (2024). Enhancing Thermal Fiducial Marker Detection: Focus on Image Processing Techniques. In: Pereira, A.I., et al. Optimization, Learning Algorithms and Applications. OL2A 2024. Communications in Computer and Information Science, vol 2281. Springer, Cham. https://doi.org/10.1007/978-3-031-77432-4_15
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