HDPA: Historical document processing and analysis framework

Ladislav Lenc and Jiří Martínek and Pavel Král and Vincent Christlein
Evolving Systems (2020)



Nowadays, the accessibility of digitized historical documents is extremely important to facilitate fast and efficient retrieval of historical information and knowledge extraction from such data. To provide such functionality, it is necessary to convert document images into plain text using optical character recognition (OCR). Many OCR related methods and tools have been proposed, however, they are often too complicated for a standard user, some important parts are missing or they are not available in free versions. Therefore, this paper describes a complex and flexible web framework for historical document manipulation and analysis with the main focus on OCR. The framework contains eight modules to facilitate three main tasks: image preprocessing and segmentation, creation of data for OCR model training and the OCR itself. This framework is freely available for non commercial purposes. We have experimentally evaluated this framework on real data and we have shown that this system is efficient and can save human labour in the process of annotated data preparation. Moreover, we have reached state-of-the-art OCR results



@ARTICLE{evos2020, author={Lenc, L. and Mart\'inek, J. and Kr\'al, P. and Nicolao, A. and Christlein, V.}, title={{HDPA}: {H}istorical document processing and analysis framework}, journal={Evolving Systems}, year={2020}, pages={1-14}, doi={10.1007/s12530-020-09343-4}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085283956&doi=10.1007%2fs12530-020-09343-4&partnerID=40&md5=cffdd78325914bf7f17a28c5330f14c0}, document_type={Article}, issn={1868-6478}, publisher={Springer}, note={Received: 20 December 2019, Accepted: 23 April 2020, Published: 20 May 2020} }
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