Writer identification in old music manuscripts using Contour-Hinge feature and dimensionality reduction with an autoencoder

Masahiro Niitsuma, Lambert Schomaker, Jean Paul Van Oosten, Yo Tomita

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Although most of the previous studies in writer identification in music scores assumed successful prior staff-line removal, this assumption does not hold when the music scores suffer from a certain level of degradation or deformation. The impact of staff-line removal on the result of writer identification in such documents is rather vague. In this study, we propose a novel writer identification method that requires no staff-line removal and no segmentation. Staff-line removal is virtually achieved without image processing, by dimensionality reduction with an autoencoder in Contour-Hinge feature space. The experimental result with a wide range of music manuscripts shows the proposed method can achieve favourable results without prior staff-line removal.

Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns - 15th International Conference, CAIP 2013, Proceedings
Pages555-562
Number of pages8
EditionPART 2
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013 - York, United Kingdom
Duration: 2013 Aug 272013 Aug 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8048 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013
Country/TerritoryUnited Kingdom
CityYork
Period13/8/2713/8/29

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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