Robust and high-performance methods for layout analysis in OCR-D

该项目旨在提高历史文件布局分析的质量和稳健性，从而确保其大规模数字化的能力。为了实现这一目标，将优化和扩展现有的方法，并整合有前途的新方法。首先，基于样本的分析书目的书籍印刷在德语国家在16日，17日和18日世纪（VD）将有助于识别（和量化）的文件，现有的布局分析方法的结果仍然是不够的。同样，将确定和统一适当的培训数据，并更有效地组织数据的编制和生成。工作的主要重点是进一步发展布局分析的补充方法。一方面，通过优化通用方法和模型，在VD中实现尽可能多的文件的广泛覆盖。另一方面，这将辅之以有助于具体解决已查明的弱点的办法，办法是大大提高方法和模型对新材料和挑战的适应性。此外，还（进一步）开发了算法，以便以基于规则的方式优化不同深度学习方法的结果。这些发展将伴随着一个详细的评估，科学标准的指标和布局评估工具将分别实施和集成在OCR-D中。最后但并非最不重要的是，必须确保所有程序都配备了模块化组件，并为各个处理步骤配备了OCR-D接口。这将使各种程序能够灵活结合，以取得尽可能好的结果，并确保对新发展的适应性和可持续性。

The project aims to improve the quality and robustness of layout analysis for historical documents and thus ensure their aptitude for mass digitization. To achieve this, existing approaches will be optimized and extended, and promising new methods will be integrated. First, a sample-based analysis of the bibliography of books printed in the German-speaking countries in the 16th, 17th and 18th century (VD) will serve to identify (and quantify) those classes of documents for which the results of existing methods for layout analysis are still insufficient. Likewise, suitable training data will be identified and harmonized, and their preparation and generation will be organized more efficiently. The main focus of the work is the further development of complementary methods for layout analysis. On the one hand, a broad coverage for as many documents as possible in the VD is to be achieved by optimizing generic methods and models. On the other hand, this will be complemented by approaches that help to specifically address identified weaknesses by significantly improving the adaptability of the methods and models for new materials and challenges. Furthermore, heuristics are (further) developed in order to optimize the results of different deep learning methods in a rule-based manner. The developments will be accompanied by a detailed evaluation for which scientific standard metrics and tools for layout evaluation will be implemented and integrated in OCR-D, respectively. Last but not least, it must be ensured that all procedures are equipped as modular components with OCR-D interfaces for individual processing steps. This will allow the flexible combination of the procedures to achieve the best possible results and ensure adaptability and sustainability with regard to new developments.