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dc.contributor.authorHsu, Ke-Lingen_US
dc.contributor.authorWu, Yu-Chunen_US
dc.contributor.authorChuang, Yu-Chengen_US
dc.contributor.authorChow, Chi-Waien_US
dc.contributor.authorLiu, Yangen_US
dc.contributor.authorLiao, Xin-Lanen_US
dc.contributor.authorLin, Kun-Hsienen_US
dc.contributor.authorChen, Yi-Yuanen_US
dc.date.accessioned2020-03-02T03:23:27Z-
dc.date.available2020-03-02T03:23:27Z-
dc.date.issued2020-01-20en_US
dc.identifier.issn1094-4087en_US
dc.identifier.urihttp://dx.doi.org/10.1364/OE.28.002427en_US
dc.identifier.urihttp://hdl.handle.net/11536/153734-
dc.description.abstractWe demonstrate a visible light communication (VLC) system using light emitting diode (LED) backlight display panel and mobile-phone complementary-metal-oxide-semiconductor (CMOS) camera. The panel is primarily used for displaying advertisements. By modulating its backlight, dynamic contents (i.e. secondary information) can be transmitted wirelessly to users based on rolling shutter effect (RSE) of the CMOS camera. As different display content will be displayed on the panel, the VLC performance is significantly limited if the noise-ratio (NR) is too high. Here, we propose and demonstrate a CMOS RSE pattern demodulation scheme using grayscale value distribution (GVD) and machine learning algorithm (MLA) to significantly enhance the demodulation. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreementen_US
dc.language.isoen_USen_US
dc.titleCMOS camera based visible light communication (VLC) using grayscale value distribution and machine learning algorithmen_US
dc.typeArticleen_US
dc.identifier.doi10.1364/OE.28.002427en_US
dc.identifier.journalOPTICS EXPRESSen_US
dc.citation.volume28en_US
dc.citation.issue2en_US
dc.citation.spage2427en_US
dc.citation.epage2432en_US
dc.contributor.department光電工程學系zh_TW
dc.contributor.departmentDepartment of Photonicsen_US
dc.identifier.wosnumberWOS:000513232200129en_US
dc.citation.woscount0en_US
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