https://oldena.lpnu.ua/handle/ntb/52439| Title: | Embedded Vision Modules for Text Recognition and Fiducial Markers Tracking |
| Authors: | Gorovyi, Ievgen Vovk, Vitalii Shevchenko, Maksim Zozulia, Valerii Sharapov, Dmytro |
| Affiliation: | It-Jim |
| Bibliographic description (Ukraine): | Embedded Vision Modules for Text Recognition and Fiducial Markers Tracking / Ievgen Gorovyi, Vitalii Vovk, Maksim Shevchenko, Valerii Zozulia, Dmytro Sharapov // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 534–537. — (Machine Vision and Pattern Recognition). |
| Bibliographic description (International): | Embedded Vision Modules for Text Recognition and Fiducial Markers Tracking / Ievgen Gorovyi, Vitalii Vovk, Maksim Shevchenko, Valerii Zozulia, Dmytro Sharapov // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 534–537. — (Machine Vision and Pattern Recognition). |
| Is part of: | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 |
| Conference/Event: | IEEE second international conference "Data stream mining and processing" |
| Issue Date: | 28-Feb-2018 |
| Publisher: | Lviv Politechnic Publishing House |
| Place of the edition/event: | Львів |
| Temporal Coverage: | 21-25 August 2018, Lviv |
| Keywords: | computer vision Raspberry Pi fiducial markers tracking text recognition |
| Number of pages: | 4 |
| Page range: | 534-537 |
| Start page: | 534 |
| End page: | 537 |
| Abstract: | In the paper, two examples of embedded vision modules are described. Firstly, it is demonstrated how fiducial marker tracking algorithm can be adopted for operation on Raspberry Pi. Usage of proposed ideas allows to achieve around 60fps speed of binary marker tracking. Secondly, we describe the problem of text detection and recognition in outdoor environment. Experimental results indicate on acceptable results and good potential to provide low-cost and efficient embedded vision system for this purpose. Technical details of both embedded vision modules are comprehensively discussed. |
| URI: | https://ena.lpnu.ua/handle/ntb/52439 |
| ISBN: | © Національний університет „Львівська політехніка“, 2018 © Національний університет „Львівська політехніка“, 2018 |
| Copyright owner: | © Національний університет “Львівська політехніка”, 2018 |
| URL for reference material: | https://www.raspberrypi.org |
| References (Ukraine): | [1] R. Szeliski, Computer vision: Algorithms and Applications. London etc.: Springer, Sept, 2010. [2] D. Baggio, S. Emami, D. Escriva, K. Ievgen, J. Saragih and R. Shikrot, Mastering OpenCV 3 - Second Edition. Birmingham: Packt Publishing Ltd, Apr, 2017. [3] https://www.raspberrypi.org [4] A. Dziri, M. Duranton, and R. Chapuis, “Real-time multiple objects tracking on Raspberry-Pi-based smart embedded camera,” Journal of Electronic Imaging, vol. 25(4), 2016 [5] James Cooper et. al., “A Raspberry Pi 2-based Stereo Camera Depth Meter,” International Conference on Machine Vision Applications, Nagoya, Japan, pp. 274-277, May 8-12, 2017. [6] Gang Jun Tu, Mikkel Kragh Hansen, Per Kryger, and Peter Ahrendt, “Automatic behaviour analysis system for honeybees using computer vision,” Computers and Electronics in Agriculture, vol. 122, pp. 10–18, 2016. [7] R. Mo, and A. Shaout, “Portable Facial Recognition Jukebox Using Fisherfaces (Frj),” International Journal of Advanced Computer Science and Applications, vol. 7, no. 3, pp. 9-14, 2016. [8] K. Sri Sasikala, and Shakeel Ahmed, “Implementation of Number Plate Extraction for Security System using Raspberry Pi Processor,” International Journal of Engineering Research & Technology (IJERT), vol. 5, iss. 03, pp. 317-321, March-2016. [9] Gurjashan Singh Pannu, Mohammad Dawud Ansari, and Pritha Gupta, “Design and Implementation of Autonomous Car using Raspberry Pi,” International Journal of Computer Applications, vol. 113, no. 9, pp. 22-29, March 2015. [10] Rizqi Andry Ardiansyah, “Design of An Electronic Narrator on Assistant Robot for Blind People,” MATEC Web of Conferences, 42: 03013, 2016. [11] Rafael Munoz-Salinas, Manuel J. Marin-Jimenez, Enrique YeguasBolivar, and R. Medina-Carnicer, “Mapping and localization from planar markers”, Pattern Recognition, vol. 73, pp. 158-171, 2018. [12] K. Horak, and L. Zalud, “Image Processing on Raspberry Pi in Matlab,” Advances in intelligent systems and computing, p. 25, 4 November 2015. [13] A. Babinec, L. Jurisica, P. Hubinsky, and F. Duchon, “Visual Localization of Mobile Robot Using Artificial Markers,” Procedia Engineering, vol. 96, pp. 1-9, 2014. [14] Ievgen M. Gorovyi, and Dmytro S. Sharapov, “Advanced Image Tracking Approach for Augmented Reality Applications,” Signal Processing Symposium (SPSympo-2017), 12-14 September, Jachranka, Poland, pp.266-270, 2017. [15] Sherin M. Youssef, and Rana M. Salem, “Automated barcode recognition for smart identification and inspection automation,” Expert Syst. Appl., vol. 33, pp. 968-977, 2007. [16] C. Ozgur, C. Alias, and B. Noche, "Comparing sensor-based and camera-based approaches to recognizing the occupancy status of the load handling device of forklift trucks,” Logist. J. Proc., pp. 1-9, 2016. [17] C. Alias, C. Ozgur and B. Noche, “Monitoring production and logistics processes with the help of industrial image processing,” 27th Annual POMS Conference 2016, Orlando (FL), USA, 2016. S. Garrido-Jurado, R. Muñoz-Salinas, F. J. Madrid-Cuevas, and M. J. Marín-Jiménez, “Automatic generation and detection of highly reliable fiducial markers under occlusion,” Pattern Recognition, vol. 47, iss. 6, pp. 2280–2292, June 2014. [18] L. Neumann and J. Matas, “Real-Time Lexicon-Free Scene Text Localization and Recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 38, no. 9, pp. 1872-1885, 2016. [19] L. Neumann and J. Matas, “Text Localization in Real-World Images Using Efficiently Pruned Exhaustive Search,” ICDAR Proc. International Conference on Document Analysis and Recognition, pp. 687-691, Sept, 2011. [20] R. Smith, “An Overview of the Tesseract OCR Engine,” ICDAR Proc. Ninth Int. Conference on Document Analysis and Recognition , pp. 629-633, 2007. |
| References (International): | [1] R. Szeliski, Computer vision: Algorithms and Applications. London etc., Springer, Sept, 2010. [2] D. Baggio, S. Emami, D. Escriva, K. Ievgen, J. Saragih and R. Shikrot, Mastering OpenCV 3 - Second Edition. Birmingham: Packt Publishing Ltd, Apr, 2017. [3] https://www.raspberrypi.org [4] A. Dziri, M. Duranton, and R. Chapuis, "Real-time multiple objects tracking on Raspberry-Pi-based smart embedded camera," Journal of Electronic Imaging, vol. 25(4), 2016 [5] James Cooper et. al., "A Raspberry Pi 2-based Stereo Camera Depth Meter," International Conference on Machine Vision Applications, Nagoya, Japan, pp. 274-277, May 8-12, 2017. [6] Gang Jun Tu, Mikkel Kragh Hansen, Per Kryger, and Peter Ahrendt, "Automatic behaviour analysis system for honeybees using computer vision," Computers and Electronics in Agriculture, vol. 122, pp. 10–18, 2016. [7] R. Mo, and A. Shaout, "Portable Facial Recognition Jukebox Using Fisherfaces (Frj)," International Journal of Advanced Computer Science and Applications, vol. 7, no. 3, pp. 9-14, 2016. [8] K. Sri Sasikala, and Shakeel Ahmed, "Implementation of Number Plate Extraction for Security System using Raspberry Pi Processor," International Journal of Engineering Research & Technology (IJERT), vol. 5, iss. 03, pp. 317-321, March-2016. [9] Gurjashan Singh Pannu, Mohammad Dawud Ansari, and Pritha Gupta, "Design and Implementation of Autonomous Car using Raspberry Pi," International Journal of Computer Applications, vol. 113, no. 9, pp. 22-29, March 2015. [10] Rizqi Andry Ardiansyah, "Design of An Electronic Narrator on Assistant Robot for Blind People," MATEC Web of Conferences, 42: 03013, 2016. [11] Rafael Munoz-Salinas, Manuel J. Marin-Jimenez, Enrique YeguasBolivar, and R. Medina-Carnicer, "Mapping and localization from planar markers", Pattern Recognition, vol. 73, pp. 158-171, 2018. [12] K. Horak, and L. Zalud, "Image Processing on Raspberry Pi in Matlab," Advances in intelligent systems and computing, p. 25, 4 November 2015. [13] A. Babinec, L. Jurisica, P. Hubinsky, and F. Duchon, "Visual Localization of Mobile Robot Using Artificial Markers," Procedia Engineering, vol. 96, pp. 1-9, 2014. [14] Ievgen M. Gorovyi, and Dmytro S. Sharapov, "Advanced Image Tracking Approach for Augmented Reality Applications," Signal Processing Symposium (SPSympo-2017), 12-14 September, Jachranka, Poland, pp.266-270, 2017. [15] Sherin M. Youssef, and Rana M. Salem, "Automated barcode recognition for smart identification and inspection automation," Expert Syst. Appl., vol. 33, pp. 968-977, 2007. [16] C. Ozgur, C. Alias, and B. Noche, "Comparing sensor-based and camera-based approaches to recognizing the occupancy status of the load handling device of forklift trucks," Logist. J. Proc., pp. 1-9, 2016. [17] C. Alias, C. Ozgur and B. Noche, "Monitoring production and logistics processes with the help of industrial image processing," 27th Annual POMS Conference 2016, Orlando (FL), USA, 2016. S. Garrido-Jurado, R. Muñoz-Salinas, F. J. Madrid-Cuevas, and M. J. Marín-Jiménez, "Automatic generation and detection of highly reliable fiducial markers under occlusion," Pattern Recognition, vol. 47, iss. 6, pp. 2280–2292, June 2014. [18] L. Neumann and J. Matas, "Real-Time Lexicon-Free Scene Text Localization and Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 38, no. 9, pp. 1872-1885, 2016. [19] L. Neumann and J. Matas, "Text Localization in Real-World Images Using Efficiently Pruned Exhaustive Search," ICDAR Proc. International Conference on Document Analysis and Recognition, pp. 687-691, Sept, 2011. [20] R. Smith, "An Overview of the Tesseract OCR Engine," ICDAR Proc. Ninth Int. Conference on Document Analysis and Recognition , pp. 629-633, 2007. |
| Content type: | Conference Abstract |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference |
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2018_Gorovyi_I-Embedded_Vision_Modules_534-537.pdf | 276.77 kB | Adobe PDF | View/Open | |
| 2018_Gorovyi_I-Embedded_Vision_Modules_534-537__COVER.png | 1.47 MB | image/png | View/Open |
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