Počet záznamů: 1

A framework for virtual restoration of ancient documents by combination of multispectral and 3D imaging

  1. 1.
    0350358 - UTIA-B 2011 RIV IT eng C - Konferenční příspěvek (zahraniční konf.)
    Bianco, G. - Bruno, F. - Tonazzini, A. - Salerno, E. - Savino, P. - Zitová, Barbara - Šroubek, Filip - Console, E.
    A framework for virtual restoration of ancient documents by combination of multispectral and 3D imaging.
    Eurographics Italian Chapter Conference. Janov: The Eurographics Association, 2010 - (Puppo, E.; Brogni, A.; de Floriani, L.), s. 1-7. ISBN 978-3-905673-80-7.
    [Eurographics Italian Chapter Conference. Janov (IT), 18.11.2010-19.11.2010]
    Grant CEP: GA MŠk 1M0572; GA ČR GA102/08/1593
    Výzkumný záměr: CEZ:AV0Z10750506
    Klíčová slova: Image Processing Application * Document Capture * Document Analysis
    Kód oboru RIV: JD - Využití počítačů, robotika a její aplikace
    http://library.utia.cas.cz/separaty/2010/ZOI/zitova-a framework for virtual restoration of ancient documents by combination of multispectral and 3d imaging.pdf http://library.utia.cas.cz/separaty/2010/ZOI/zitova-a framework for virtual restoration of ancient documents by combination of multispectral and 3d imaging.pdf

    Our paper presents a framework for virtual restoration of ancient documents based on a combination of multispectral acquisition, 3D imaging and digital image analysis. The proposed framework consists of several steps. First, digital representations of the documents are acquired as multispectral images and 3D surface maps, the latter reconstructed by a structured light technique. A multispectral camera and a digital projector are used in triangular configuration for 2D and 3D data acquisition. Then the multispectral images are registered against possible misalignments, and the 3D surface representation is used to correct geometrical distortions. Document flattening is then performed by 3D surface parameterization and texture mapping. Statistical techniques of decorrelation are applied to extract individual context parts of the document patterns (stamp, text, etc.) and to attenuate interferences. The processed data are then binarized by the proper segmentation technique.
    Trvalý link: http://hdl.handle.net/11104/0190377