Un innovativo Graphic Matching System per la ricerca in database di manoscritti antichi

The paper outlines a pattern recognition process, which uses a graphic matching algorithm based on a shape contour recognition function without the need to apply segmentation. The process starts from the identification of a Region of Interest (ROI) within the image. The ROI is then managed for the c...

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Main Authors: Nicola Barbuti, Stefano Ferilli, Tommaso Caldarola
Format: Article
Language:English
Published: University of Bologna 2018-11-01
Series:Umanistica Digitale
Subjects:
Online Access:https://umanisticadigitale.unibo.it/article/view/8144
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spelling doaj-79d9541c1cc0478cabda7e4543e520fd2020-11-24T21:38:49ZengUniversity of BolognaUmanistica Digitale2532-88162018-11-012310.6092/issn.2532-8816/81447535Un innovativo Graphic Matching System per la ricerca in database di manoscritti antichiNicola Barbuti0Stefano Ferilli1Tommaso Caldarola2Università degli Studi di Bari Aldo MoroUniversità degli Studi di Bari Aldo MoroD.A.BI.MUS S.r.l.The paper outlines a pattern recognition process, which uses a graphic matching algorithm based on a shape contour recognition function without the need to apply segmentation. The process starts from the identification of a Region of Interest (ROI) within the image. The ROI is then managed for the creation of the shape model then used to perform searches for similar models in one or more target images. The system has been developed and tested with the aim of proposing an innovative approach in the research and retrieval of information in digital libraries related to ancient manuscript and printed documentation. This approach is based on the application to the data humanities of the fourth knowledge paradigm that underlies data science. Following this approach, the algorithm is used to deduce new research hypotheses through the discovery of models directly inferred from large digital libraries.https://umanisticadigitale.unibo.it/article/view/8144Graphic MatchingPattern RecognitionDigital LibrariesData ScienceData HumanitiesManuscriptsDigital Recognition
collection DOAJ
language English
format Article
sources DOAJ
author Nicola Barbuti
Stefano Ferilli
Tommaso Caldarola
spellingShingle Nicola Barbuti
Stefano Ferilli
Tommaso Caldarola
Un innovativo Graphic Matching System per la ricerca in database di manoscritti antichi
Umanistica Digitale
Graphic Matching
Pattern Recognition
Digital Libraries
Data Science
Data Humanities
Manuscripts
Digital Recognition
author_facet Nicola Barbuti
Stefano Ferilli
Tommaso Caldarola
author_sort Nicola Barbuti
title Un innovativo Graphic Matching System per la ricerca in database di manoscritti antichi
title_short Un innovativo Graphic Matching System per la ricerca in database di manoscritti antichi
title_full Un innovativo Graphic Matching System per la ricerca in database di manoscritti antichi
title_fullStr Un innovativo Graphic Matching System per la ricerca in database di manoscritti antichi
title_full_unstemmed Un innovativo Graphic Matching System per la ricerca in database di manoscritti antichi
title_sort un innovativo graphic matching system per la ricerca in database di manoscritti antichi
publisher University of Bologna
series Umanistica Digitale
issn 2532-8816
publishDate 2018-11-01
description The paper outlines a pattern recognition process, which uses a graphic matching algorithm based on a shape contour recognition function without the need to apply segmentation. The process starts from the identification of a Region of Interest (ROI) within the image. The ROI is then managed for the creation of the shape model then used to perform searches for similar models in one or more target images. The system has been developed and tested with the aim of proposing an innovative approach in the research and retrieval of information in digital libraries related to ancient manuscript and printed documentation. This approach is based on the application to the data humanities of the fourth knowledge paradigm that underlies data science. Following this approach, the algorithm is used to deduce new research hypotheses through the discovery of models directly inferred from large digital libraries.
topic Graphic Matching
Pattern Recognition
Digital Libraries
Data Science
Data Humanities
Manuscripts
Digital Recognition
url https://umanisticadigitale.unibo.it/article/view/8144
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AT stefanoferilli uninnovativographicmatchingsystemperlaricercaindatabasedimanoscrittiantichi
AT tommasocaldarola uninnovativographicmatchingsystemperlaricercaindatabasedimanoscrittiantichi
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