Musicologist-driven writer identification in early music manuscripts

Recent renewed interest in computational writer identification has resulted in an increased number of publications. In relation to historical musicology its application has so far been limited. One of the obstacles seems to be that the clarity of the images from the scans available for computational...

Full description

Saved in:
Bibliographic Details
Published in:Multimedia tools and applications Vol. 75; no. 11; pp. 6463 - 6479
Main Authors: Niitsuma, Masahiro, Schomaker, Lambert, Oosten, Jean-Paul van, Tomita, Yo, Bell, David
Format: Journal Article
Language:English
Published: New York Springer US 01-06-2016
Springer Nature B.V
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Recent renewed interest in computational writer identification has resulted in an increased number of publications. In relation to historical musicology its application has so far been limited. One of the obstacles seems to be that the clarity of the images from the scans available for computational analysis is often not sufficient. In this paper, the use of the Hinge feature is proposed to avoid segmentation and staff-line removal for effective feature extraction from low quality scans. The use of an auto encoder in Hinge feature space is suggested as an alternative to staff-line removal by image processing, and their performance is compared. The result of the experiment shows an accuracy of 87 % for the dataset containing 84 writers’ samples, and superiority of our segmentation and staff-line removal free approach. Practical analysis on Bach’s autograph manuscript of the Well-Tempered Clavier II (Additional MS. 35021 in the British Library, London) is also presented and the extensive applicability of our approach is demonstrated.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-015-2583-8