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Signature detection as a way to recognise historical parish register structure
- Source :
- HIP 2019, HIP 2019, Sep 2019, Sydney, Australia. pp.54-59, ⟨10.1145/3352631.3352636⟩, HIP@ICDAR
- Publication Year :
- 2019
- Publisher :
- HAL CCSD, 2019.
-
Abstract
- International audience; This article deals with the analysis of pages of French parish registers from 16th to 18th century. These documents are structured in paragraphs called acts. Each act contains valuable demographic information that can be useful to genealogists willing to find information about their ancestors. The first step toward parish register analysis consists of delimiting each act. But these documents are so poorly-structured that the visual separation between the acts is not always clearly visible. One of the main visual indication of separation is the signature of the priest at the end of each act. In this work, we propose to train and compare several u-shaped neural networks for signature detection. We also propose a rule-based system for segmentation into acts and evaluate the impact of signature detection at act level. CCS CONCEPTS • Applied computing → Document analysis.
- Subjects :
- Structure (mathematical logic)
signature detection
Information retrieval
Artificial neural network
Structure analysis
Computer science
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
020207 software engineering
02 engineering and technology
neural networks
Signature (logic)
structure analysis
parish registers
Parish register
[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing
Signature detection
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Segmentation
[INFO]Computer Science [cs]
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- HIP 2019, HIP 2019, Sep 2019, Sydney, Australia. pp.54-59, ⟨10.1145/3352631.3352636⟩, HIP@ICDAR
- Accession number :
- edsair.doi.dedup.....555391cf0ac20fe86ab06bd7bd397b31