An Intelligent Semi-Automatic Workflow for Optical Character Recognition of Historical Printings
Optical Character Recognition (OCR) on historical printings is a challenging task mainly due to the complexity of the layout and the highly variant typography. Nevertheless, in the last few years great progress has been made in the area of historical OCR resulting in several powerful open-source too...
| Main Author: | |
|---|---|
| Format: | Doctoral Thesis |
| Language: | English |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/docId/20923 http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-209239 https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-209239 https://doi.org/10.25972/OPUS-20923 https://opus.bibliothek.uni-wuerzburg.de/files/20923/Reul_Christian_Dissertation.pdf |
Internet
https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/docId/20923http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-209239
https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-209239
https://doi.org/10.25972/OPUS-20923
https://opus.bibliothek.uni-wuerzburg.de/files/20923/Reul_Christian_Dissertation.pdf