Automatic Handwriting Feature Extraction, Analysis and Visualization in the Context of Digital Palaeography

Liang, Y. and Fairhurst, Michael and Guest, Richard and Erbilek, Meryem (2016) Automatic Handwriting Feature Extraction, Analysis and Visualization in the Context of Digital Palaeography. International Journal of Pattern Recognition and Artificial Intelligence, 30 (04). p. 1653001. ISSN 0218-0014. (doi:https://doi.org/10.1142/S0218001416530013) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

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Abstract

Digital palaeography is an emerging research area which aims to introduce digital image processing techniques into palaeographic analysis for the purpose of providing objective quantitative measurements. This paper explores the use of a fully automated handwriting feature extraction, visualization, and analysis system for digital palaeography which bridges the gap between traditional and digital palaeography in terms of the deployment of feature extraction techniques and handwriting metrics. We propose the application of a set of features, more closely related to conventional palaeographic assesment metrics than those commonly adopted in automatic writer identification. These features are emprically tested on two datasets in order to assess their effectiveness for automatic writer identification and aid attribution of individual handwriting characteristics in historical manuscripts. Finally, we introduce tools to support visualization of the extracted features in a comparative way, showing how they can best be exploited in the implementation of a content-based image retrieval (CBIR) system for digital archiving. Read More: http://www.worldscientific.com/doi/abs/10.1142/S0218001416530013

Item Type: Article
Uncontrolled keywords: Digital palaeography; manuscript exploration; image analysis
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Tina Thompson
Date Deposited: 17 May 2016 13:45 UTC
Last Modified: 29 Sep 2016 09:11 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/55474 (The current URI for this page, for reference purposes)
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