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International Theoretical Science Journal
Volume 58 >>> № 4 JULY — AUGUST 2022
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UDC 004.93.12
S. Yaremenko, Iu. Krak1


1 Taras Shevchenko National University of Kyiv, Kyiv, Ukraine

 yaserg555@gmail.com

2 Taras Shevchenko National University of Kyiv, Kyiv, Ukraine, and V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine

 yuri.krak@gmail.com

DETERMINING THE CENTROID OF A LASER SPOT IN THE PLANE OF A MULTIMEDIA
SHOOTING GALLERY SENSOR BASED ON THE METHODS OF INTERPOLATION
AND FILTERING OF THE IMAGE FRAGMENT

Abstract. The authors consider the problem of determining the position of the centroid of a laser spot on the plane of the photosensor in a multimedia shooting gallery. A two-stage approach to solving this problem is proposed. The possibilities of increasing the accuracy of determining the centroid by explicitly highlighting the contours of the spot (2nd stage of processing) instead of determining the boundaries of the laser spot through threshold binarization are investigated. The approaches to determining the contours of the spot are analyzed. To solve the problem, the scale of the image fragment was increased through the interpolation of new points. The possibilities of highlighting the contour of the spot by processing a fragment of the image with filters of low and high frequencies are investigated. A comparative assessment of the accuracy of the basic algorithm and that of the modified version was carried out, which showed that the modified algorithm increases the accuracy of determining the centroid by 30%. Higher accuracy was achieved because the modified method made it possible to find the explicit contours of the spot.

Keywords: multimedia shooting range, laser spot, contour, centroid, digital image filters.


FULL TEXT

REFERENCES

  1. Jedrasiak K., Daniec K., Sobel D., Bereska D., Nawrat A. The concept of development and test results of the multimedia shooting detection system. Proc. 2016 Future Technologies Conference (FTC) (6–7 December 2016, San Francisco, CA, USA). San Francisco, 2016. P. 1057–1064. https://doi.org/10.1109/FTC.2016.7821734.

  2. Laser Shot, Inc. URL: http://www.lasershot.com/government-military .

  3. Sviderski W., Glogowski T., Hlosta P., Stepniak S. IR detection of impact places of projectiles in the training system “SNIEZNIK.” Problems of Mechatronics. Armament, Aviation, Safety Engineering. 2018. Vol. 9, Iss. 2. P. 99–110. https://doi.org/10.5604/01.3001.0012.1104.

  4. OpenCV team. URL: https://docs.opencv.org .

  5. Zakaria N.F., Zulkifley M.A., Mustafa M.M., Rohana A.K.. A review on laser spot detection system based on image processing techniques. Journal of Theoretical and Applied Information Technology. 2014. Vol. 70, Iss. 2. P. 333–344.

  6. Fadhil A.F., Fatih M.M. Laser spot detection and tracking. ZANCO Journal of Pure and Applied Sciences. 2016. Vol. 28, Iss. 2. P. 615–623.

  7. Aguilar W.G., Castro P., Caballeros J., Segarra D. Homography and morphological detection-based virtual shooting range. In: Ubiquitous Networking. UNet 2018. Boudriga N., Alouini M-S., Rekhis S., Sabir E., Pollin S. (Eds.). Lecture Notes in Computer Science. 2018. Vol. 11277. P. 267–272. .

  8. Wang H., Hui L., Zhang J. Research on spot of CCD subdivided locating methods in laser triangulation displacement measurement. Proc. SPIE. 2017. Vol. 10256. https://doi.org/10.1117/12.2257635.

  9. Guthe S.A., Soni P.M. Target shooting training and instructive system model using Python. International Journal of Engineering Research & Technology (IJERT). 2016. Vol. 5, Iss. 05. P. 594–597. http://dx.doi.org/10.17577/IJERTV5IS050902.

  10. Barmak A.V., Krak Iu.V., Manziuk E.A., Kasianiuk V.S. Information technology of separating hyperplanes synthesis for linear classifiers. J. Autom. Inf. Sci. 2019. Vol. 51, Iss. 5. P. 54–64. https://doi.org/10.1615/JAutomatInfScien.v51.i5.50.

  11. Krak Iu.V., Kudin G.I., Kulyas A.I. Multidimensional scaling by means of pseudoinverse operations. Cybernetics and Systems Analysis. 2019. Vol. 55, N 1. P. 22–29. https://doi.org/ 10.1007/s10559-019-00108-9.

  12. Abdulrahman H., Magnier B., Montesinos P. From contours to ground truth: How to evaluate edge detectors by filtering. Journal of WSCG. 2017. Vol. 25, Iss. 2. P. 133–142.

  13. Yaremenko S., Krak Iu. Determination of the position of the laser spot in the plane of the photo sensor of the multimedia shooting gallery. Proc. EUROCON 2021 — 19th IEEE International Conference on Smart Technologies (6–8 July 2021, Lviv, Ukraine). Lviv, 2021. P. 531–536. https://doi.org/10.1109/EUROCON52738.2021.9535549.

  14. Chen Q., Sun Q., Heng P., Xia D. A double-threshold image binarization method based on edge detector. Pattern Recognition. 2008. Vol. 41, Iss. 4. P. 1254–1267. https://doi.org/10.1016/j.patcog.2007.09.007.

  15. Gonzalez R., Woods R. Digital image processing [Russian translaion]. Moscow: Technosphera, 2012. 1104 p.

  16. Freedman G., Fattal R. Image and video upscaling from local self-examples. ACM Trans. Graph. 2011. Vol. 30, Iss. 2. P. 1–11. https://doi.org/10.1145/1944846.1944852.

  17. Prasad R., Sresh S. A review on edge detection algorithms. International Journal of Mechanical Engineering and Computer Applications. 2016. N 1. P. 7–11.

  18. Balabantaray B.K., Sahu O.P., Mishra N. A quantitative performance analysis of edge det.ctors with hybrid edge detector. Journal of Computers. 2017. Vol. 12, N 2. P. 165–173.




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