System Description of CITlab's Recognition & Retrieval Engine for ICDAR2017 Competition on Information Extraction in Historical Handwritten Records

Tobias Strauß; Max Weidemann; Johannes Michael; Gundram Leifert; Tobias Grüning; Roger Labahn

System Description of CITlab's Recognition & Retrieval Engine for ICDAR2017 Competition on Information Extraction in Historical Handwritten Records

Information Retrieval 2018-04-27 v1

Authors: Tobias Strauß , Max Weidemann , Johannes Michael , Gundram Leifert , Tobias Grüning , Roger Labahn

Abstract

We present a recognition and retrieval system for the ICDAR2017 Competition on Information Extraction in Historical Handwritten Records which successfully infers person names and other data from marriage records. The system extracts information from the line images with a high accuracy and outperforms the baseline. The optical model is based on Neural Networks. To infer the desired information, regular expressions are used to describe the set of feasible words sequences.

Keywords

information extraction historical handwritten records recognition system retrieval engine neural networks regular expressions

Cite

@article{arxiv.1804.09943,
  title  = {System Description of CITlab's Recognition & Retrieval Engine for ICDAR2017 Competition on Information Extraction in Historical Handwritten Records},
  author = {Tobias Strauß and Max Weidemann and Johannes Michael and Gundram Leifert and Tobias Grüning and Roger Labahn},
  journal= {arXiv preprint arXiv:1804.09943},
  year   = {2018}
}

System Description of CITlab's Recognition & Retrieval Engine for ICDAR2017 Competition on Information Extraction in Historical Handwritten Records

Abstract

Keywords

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