Automatic Writer Identification in Historical Documents: A Case Study
In recent years, Automatic Writer Identification (AWI) has received a lot of attention in the document analysis community. However, most research has been conducted on contemporary benchmark sets. These datasets typi...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | deu |
| Published: |
Forschungsverbund Marbach Weimar Wolfenbüttel
2016-07-01
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| Series: | Zeitschrift für digitale Geisteswissenschaften |
| Subjects: | |
| Online Access: | http://www.zfdg.de/node/184 |
| Summary: | In recent years, Automatic Writer Identification (AWI) has received a lot
of attention in the document analysis community. However, most research
has been conducted on contemporary benchmark sets. These datasets
typically do not contain any noise or artefacts caused by the conversion
methodology. This article analyses how current state-of-the-art methods
in writer identification perform on historical documents. In contrast to
contemporary documents, historical data often contain artefacts such as
holes, rips, or water stains which make reliable identification
error-prone. Experiments were conducted on two large letter collections
with known authenticity and promising results of 82% and 89% TOP-1
accuracy were achieved. |
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| ISSN: | 2510-1358 |