Presentation	2014-03-06 Paper Finger Print Identification Using Locally Zero-mean Normalized Cross Correlation Function Ryuji MINE,
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Abstract(in English)	Paper finger print identification, which used transmission image pattern of pulp fiber as characteristic feature to identify paper, is simple and easy method. However, spots and dirty on paper decrease identification accuracy drastically. Based on the observation that paper with spot and dirt preserve its intrinsic paper finger print pattern, we incorporate the locally zero-mean normalized cross correlation function in order to identify papers. Experimental results shows the effectiveness of the proposed method.
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Keyword(in English)	Paper Finger Print / Paper Identification / Normalized Cross Correlation Function
Paper #	IMQ2013-43,IE2013-152,MVE2013-81
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Conference Information
Committee	MVE
Conference Date	2014/2/27(1days)
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Paper Information
Registration To	Media Experience and Virtual Environment (MVE)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Paper Finger Print Identification Using Locally Zero-mean Normalized Cross Correlation Function
Sub Title (in English)
Keyword(1)	Paper Finger Print
Keyword(2)	Paper Identification
Keyword(3)	Normalized Cross Correlation Function
1st Author's Name	Ryuji MINE
1st Author's Affiliation	Central Research Laboratory, Hitachi, Ltd.()
Date	2014-03-06
Paper #	IMQ2013-43,IE2013-152,MVE2013-81
Volume (vol)	vol.113
Number (no)	470
Page	pp.pp.-
#Pages	6
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