ANALYSIS OF THE POSSIBILITY OF USING MARKERS EMITTING PULSATING LIGHT IN THE TASK OF LOCALIZATION
Piotr Miś
piotr.mis.stud@pw.edu.plWarsaw University of Technology, Faculty of Automotive and Construction Machinery Engineering (Poland)
Przemysław Szulim
Warsaw University of Technology, Faculty of Automotive and Construction Machinery Engineering, Warsaw (Poland)
Abstract
This work shows the possibility of using spectral analysis in order to detect characteristic points in recorded images. The specific point is a marker in the form of a diode that flashes at a certain frequency. Main assumptions of the processing algorithm are the recording of a sequence of images and treatment change of level of brightness for each pixel as a time signal. The amplitude spectrum is determined for each time signal. The result of data processing is an amplitude image whose pixels brightness corresponding to the intensity of source of pulsating light emitting specific frequency. This new data representation is used to detect position of markers. The algorithm was re¬searched in order to select optimal marker colors and pulsation frequency. The results are described in a summary.
Keywords:
image processing, spectrum analysis, pulsating marker, localization, mobile roboticsReferences
Guan, W., Wen, S., Zhang, H., & Liu, L. (2018). A novel three-dimensional indoor localization algorithm based on visual visible light communication using single LED. In IEEE International Conference on Automation, Electronics and Electrical Engineering, AUTEEE (pp. 202–208). http://doi.org/10.1109/AUTEEE.2018.8720798
DOI: https://doi.org/10.1109/AUTEEE.2018.8720798
Google Scholar
Hassan, N. U., Naeem, A., Pasha, M. A., Jadoon, T., & Yuen, C. (2015). Indoor positioning using visible LED lights: A survey. ACM Computing Surveys, 48(2), 20:1–20:32. http://doi.org/10.1145/2835376
DOI: https://doi.org/10.1145/2835376
Google Scholar
Hong, C.-Y., Wu, Y.-Ch., Liu, Y., Chow, Ch.-W., Yeh, Ch.-H., Hsu, K.-L., Lin, D.-Ch., Liao, X.-L., Lin, K.-H., & Chen, Y.-Y. (2020). Angle-of-Arrival (AOA) Visible Light Positioning (VLP) System Using Solar Cells with Third-Order Regression and Ridge Regression Algorithms. IEEE Photonics Journal, 12(3), 7902605. http://doi.org/10.1109/JPHOT.2020.2993031
DOI: https://doi.org/10.1109/JPHOT.2020.2993031
Google Scholar
Hossen, M. S., Park, Y., & Kim, K.-D. (2015). Performance improvement of indoor positioning using light-emitting diodes and an image sensor for light-emitting diode communication. Optical Engineering, 54(4),045101. http://doi.org/10.1117/1.OE.54.4.045101
DOI: https://doi.org/10.1117/1.OE.54.4.045101
Google Scholar
Jung, S.-Y., Hann, S., & Park, C.-S. (2011). TDOA-based optical wireless indoor localization using LED ceiling lamps. IEEE Transactions on Consumer Electronics, 57(4), 1592–1597. http://doi.org/10.1109/TCE.2011.6131130
DOI: https://doi.org/10.1109/TCE.2011.6131130
Google Scholar
Kuo, Y.-S., Pannuto, P., & Dutta, P. (2014). Demo – Luxapose: Indoor positioning with mobile phones and visible light. In 20th ACM Annual International Conference on Mobile Computing and Networking, MobiCom (pp. 447–458). New York: ACM. http://doi.org/10.1145/2639108.2641747
DOI: https://doi.org/10.1145/2639108.2641747
Google Scholar
Maheepala, M., Kouzani, A. Z., & Joordens, M. A. (2020). Light-Based Indoor Positioning Systems: A Review. IEEE Sensors Journal, 20(8), 3971–3995. http://doi.org/10.1109/JSEN.2020.2964380
DOI: https://doi.org/10.1109/JSEN.2020.2964380
Google Scholar
Moon, M.-G., Choi, S.-I., Park, J., & Kim, J. Y. (2015). Indoor positioning system using LED lights and a dual image sensor. Journal of the Optical Society of Korea, 19(6), 586–591. http://doi.org/10.3807/JOSK.2015.19.6.586
DOI: https://doi.org/10.3807/JOSK.2015.19.6.586
Google Scholar
Raharijaona, T., Mignon, P., Juston, R., Kerhuel, L., & Viollet, S. (2015). HyperCube: A Small Lensless Position Sensing Device for the Tracking of Flickering Infrared LEDs. Sensors (Switzerland), 15(7), 16484–16502. http://doi.org/10.3390/s150716484
DOI: https://doi.org/10.3390/s150716484
Google Scholar
Wang, C., Wang, L., Chi, X., Liu, S., Shi, W., & Deng, J. (2015). The research of indoor positioning based on visible light communication. China Communications, 12(8), 85–92. http://doi.org/10.1109/CC.2015.7224709
DOI: https://doi.org/10.1109/CC.2015.7224709
Google Scholar
Wu, Y.-C., Hsu, K.-L., Liu, Y., Hong, Ch.-Y., Chow, Ch.-W., Yeh, Ch.-H., Liao, X.-L., Lin, K.-H., & Chen, Y.-Y. (2020). Using linear interpolation to reduce the training samples for regression based visible light positioning system. IEEE Photonics Journal, 12(2), 7901305. http://doi.org/10.1109/JPHOT.2020.2975213
DOI: https://doi.org/10.1109/JPHOT.2020.2975213
Google Scholar
Yeon Kim, B., Cho, J.-S., Park, Y., & Kim, K.-D. (2012). Implementation of indoor positioning using LED and dual PC cameras. In 4th International Conference on Ubiquitous and Future Networks, ICUFN (pp. 476–477). http://doi.org/10.1109/ICUFN.2012.6261753
DOI: https://doi.org/10.1109/ICUFN.2012.6261753
Google Scholar
Zhang, W., Chowdhury, M. I. S., & Kavehrad, M. (2014). Asynchronous indoor positioning system based on visible light communications. Optical Engineering, 53(4), 045105. http://doi.org/10.1117/1.OE.53.4.045105
DOI: https://doi.org/10.1117/1.OE.53.4.045105
Google Scholar
Authors
Piotr Miśpiotr.mis.stud@pw.edu.pl
Warsaw University of Technology, Faculty of Automotive and Construction Machinery Engineering Poland
Authors
Przemysław SzulimWarsaw University of Technology, Faculty of Automotive and Construction Machinery Engineering, Warsaw Poland
Statistics
Abstract views: 219PDF downloads: 30
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.
Similar Articles
- Muaayed F. AL-RAWI, Izz K. ABBOUD, Nasir A. AL-AWAD, PERFORMANCE ANALYSIS AND EVALUATION OF MASSIVE MIMO SYSTEM , Applied Computer Science: Vol. 16 No. 2 (2020)
- Elmehdi BENMALEK, Jamal EL MHAMDI, Abdelilah JILBAB, Atman JBARI, A COUGH-BASED COVID-19 DETECTION SYSTEM USING PCA AND MACHINE LEARNING CLASSIFIERS , Applied Computer Science: Vol. 18 No. 4 (2022)
- Konrad PIETRYKOWSKI, Tytus TULWIN, THE NONUNIFORMITY OF THE PISTON MOTION OF THE RADIAL ENGINE , Applied Computer Science: Vol. 13 No. 2 (2017)
- Marcin TOMCZYK, Barbara BOROWIK, Mariusz MIKULSKI, IDENTIFICATION OF A BACKLASH ZONE IN AN ELECTROMECHANICAL SYSTEM CONTAINING CHANGES OF A MASS INERTIA MOMENT BASED ON A WAVELET–NEURAL METHOD , Applied Computer Science: Vol. 14 No. 4 (2018)
- Zbigniew CZYŻ, Paweł KARPIŃSKI, Tacetdin SEVDIM, NUMERICAL ANALYSIS OF THE DRAG COEFFICIENT OF A MOTORCYCLE HELMET , Applied Computer Science: Vol. 14 No. 1 (2018)
- Nataliya SHABLIY, Serhii LUPENKO, Nadiia LUTSYK, Oleh YASNIY, Olha MALYSHEVSKA, KEYSTROKE DYNAMICS ANALYSIS USING MACHINE LEARNING METHODS , Applied Computer Science: Vol. 17 No. 4 (2021)
- Qingyu Liu, Roben A. Juanatas, MASK FACE INPAINTING BASED ON IMPROVED GENERATIVE ADVERSARIAL NETWORK , Applied Computer Science: Vol. 19 No. 2 (2023)
- Marian JANCZAREK, COMPUTER MODELLING OF THERMAL TECHNICAL SPACESS IN ASPECT OF HEAT TRANSFER THROUGH THE WALLS , Applied Computer Science: Vol. 14 No. 3 (2018)
- Tilla IZSÁK, László MARÁK, Mihály ORMOS, EVALUATION OF SUPPORT VECTOR MACHINE BASED STOCK PRICE PREDICTION , Applied Computer Science: Vol. 19 No. 3 (2023)
- Zbigniew CZYŻ, Paweł KARPIŃSKI, Krzysztof SKIBA, Szymon BARTKOWSKI, NUMERICAL CALCULATIONS OF WATER DROP USING A FIREFIGHTING AIRCRAFT , Applied Computer Science: Vol. 19 No. 3 (2023)
<< < 2 3 4 5 6 7 8 9 10 11 > >>
You may also start an advanced similarity search for this article.
