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  1. Електронний науковий архів Науково-технічної бібліотеки Національного університету "Львівська політехніка"
  2. Електронний архів Науково-технічної бібліотеки
  3. Матеріали конференцій
  4. Data stream mining and processing : proceedings of the IEEE second international conference
  5. Data stream mining and processing : proceedings of the IEEE second international conference

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Please use this identifier to cite or link to this item: https://oldena.lpnu.ua/handle/ntb/52439
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dc.contributor.authorGorovyi, Ievgen
dc.contributor.authorVovk, Vitalii
dc.contributor.authorShevchenko, Maksim
dc.contributor.authorZozulia, Valerii
dc.contributor.authorSharapov, Dmytro
dc.coverage.temporal21-25 August 2018, Lviv
dc.date.accessioned2020-06-19T12:04:32Z-
dc.date.available2020-06-19T12:04:32Z-
dc.date.created2018-02-28
dc.date.issued2018-02-28
dc.identifier.citationEmbedded 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).
dc.identifier.isbn© Національний університет „Львівська політехніка“, 2018
dc.identifier.isbn© Національний університет „Львівська політехніка“, 2018
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/52439-
dc.description.abstractIn 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.
dc.format.extent534-537
dc.language.isoen
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofData stream mining and processing : proceedings of the IEEE second international conference, 2018
dc.relation.urihttps://www.raspberrypi.org
dc.subjectcomputer vision
dc.subjectRaspberry Pi
dc.subjectfiducial markers
dc.subjecttracking
dc.subjecttext recognition
dc.titleEmbedded Vision Modules for Text Recognition and Fiducial Markers Tracking
dc.typeConference Abstract
dc.rights.holder© Національний університет “Львівська політехніка”, 2018
dc.contributor.affiliationIt-Jim
dc.format.pages4
dc.identifier.citationenEmbedded 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).
dc.relation.references[1] R. Szeliski, Computer vision: Algorithms and Applications. London etc.: Springer, Sept, 2010.
dc.relation.references[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.
dc.relation.references[3] https://www.raspberrypi.org
dc.relation.references[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
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[10] Rizqi Andry Ardiansyah, “Design of An Electronic Narrator on Assistant Robot for Blind People,” MATEC Web of Conferences, 42: 03013, 2016.
dc.relation.references[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.
dc.relation.references[12] K. Horak, and L. Zalud, “Image Processing on Raspberry Pi in Matlab,” Advances in intelligent systems and computing, p. 25, 4 November 2015.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[20] R. Smith, “An Overview of the Tesseract OCR Engine,” ICDAR Proc. Ninth Int. Conference on Document Analysis and Recognition , pp. 629-633, 2007.
dc.relation.referencesen[1] R. Szeliski, Computer vision: Algorithms and Applications. London etc., Springer, Sept, 2010.
dc.relation.referencesen[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.
dc.relation.referencesen[3] https://www.raspberrypi.org
dc.relation.referencesen[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
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[10] Rizqi Andry Ardiansyah, "Design of An Electronic Narrator on Assistant Robot for Blind People," MATEC Web of Conferences, 42: 03013, 2016.
dc.relation.referencesen[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.
dc.relation.referencesen[12] K. Horak, and L. Zalud, "Image Processing on Raspberry Pi in Matlab," Advances in intelligent systems and computing, p. 25, 4 November 2015.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[20] R. Smith, "An Overview of the Tesseract OCR Engine," ICDAR Proc. Ninth Int. Conference on Document Analysis and Recognition , pp. 629-633, 2007.
dc.citation.conferenceIEEE second international conference "Data stream mining and processing"
dc.citation.spage534
dc.citation.epage537
dc.coverage.placenameЛьвів
Appears in Collections:Data stream mining and processing : proceedings of the IEEE second international conference

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