Study methods of image segmentation for intelligent surveillance systems

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dc.citation.epage176
dc.citation.spage171
dc.contributor.affiliationLviv Polytechnic National University, Lviv, Ukraine
dc.contributor.authorHrytsyk, V. V.
dc.coverage.placenameLviv
dc.coverage.temporal25-27 June 2018
dc.date.accessioned2018-09-03T11:41:13Z
dc.date.available2018-09-03T11:41:13Z
dc.date.created2018-06-25
dc.date.issued2018-06-25
dc.description.abstractThe research of the machine-machine interface element is presented for the possibility of dynamic adaptation to improve the perception of the very least environment by developing a technique for adapting the robovision. The study include comparing between different threshold methods of segmentation of images of different categories.
dc.format.extent171-176
dc.format.pages6
dc.identifier.citationHrytsyk V. V. Study methods of image segmentation for intelligent surveillance systems / V. V. Hrytsyk // Computational linguistics and intelligent systems, 25-27 June 2018. — Lviv : Lviv Polytechnic National University, 2018. — Vol 2 : Workshop. — P. 171–176. — (Section II. Intelligent Systems).
dc.identifier.citationenHrytsyk V. V. Study methods of image segmentation for intelligent surveillance systems / V. V. Hrytsyk // Computational linguistics and intelligent systems, 25-27 June 2018. — Lviv : Lviv Polytechnic National University, 2018. — Vol 2 : Workshop. — P. 171–176. — (Section II. Intelligent Systems).
dc.identifier.issn2523-4013
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/42565
dc.language.isoen
dc.publisherLviv Polytechnic National University
dc.relation.ispartofComputational linguistics and intelligent systems (2), 2018
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dc.relation.referencesen6. Validation of various adaptive threshold methods of segmentation applied to follicular lymphoma digital images stained with 3,3’-Diaminobenzidine&Haematoxylin. Published online 2013 Mar 25. Access mode: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3656801/
dc.relation.referencesen7. Sauvola J, Pietikainen M. Adaptive document image binarization. Patt Recognit. 2000;33(2):225–236. doi: 10.1016/S0031-3203(99)00055-2. [] Sauvola J, Pietikainen M.Adaptive document image binarization. Patt Recognit. 2000;33(2):225–236. doi: 10.1016/S0031-3203(99)00055-2. [ Robots of tomorrow with intelligent visual capabilities. research results magazine, No 62, May 2017, 38p.
dc.relation.referencesen8. Mehmet Sezgin, Bulent Sankur. Journal of Electronic Imaging 13(1), 146–165 (January 2004), Survey over image thresholding techniques and quantitative performance evaluation
dc.relation.referencesen9. Zack, G.W., W.E. Rogers, and S.A. Latt, Automatic Measurement of Sister Chromatid Exchange Frequency. 1977. 25(7): p. 741-753.
dc.relation.referencesen10. Dronyuk, I.Development of printed packaging protection technology by means of background nets, Dronyuk, I., Nazarkevych, M, Experience of Designing and Application of CAD Systems in Microelectronics - Proceedings of the 10th International Conference, CADSM 20092009, Article number 4839864, Pages 401-403.
dc.relation.referencesen11. Cutting-edge facial recognition goes mainstream, Reasearch*eu results magazine, No 68, December 2017-January 2018, P.39
dc.relation.urihttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3656801/
dc.rights.holder© 2018 for the individual papers by the papers’ authors. Copying permitted only for private and academic purposes. This volume is published and copyrighted by its editors.
dc.subjectimage segmentation
dc.subjectthresholds
dc.subjectfuture robots
dc.titleStudy methods of image segmentation for intelligent surveillance systems
dc.typeConference Abstract

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