System Description of CITlab's Recognition & Retrieval Engine for ICDAR2017 Competition on Information Extraction in Historical Handwritten Records
This is an incremental improvement for researchers in document analysis and historical record digitization.
The paper tackled the problem of extracting person names and other data from historical handwritten marriage records, achieving high accuracy and outperforming the baseline in the ICDAR2017 competition.
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.