Development of a semi-automatic open source tool for layout analysis and region extraction and region classificiation (LAREX) of early prints.

开发半自动开源工具，用于早期印刷品的布局分析以及区域提取和区域分类（LAREX）。

• 批准号: 394329162
• 负责人: Professor Dr. Frank Puppe
• 金额: --
• 依托单位: Lehrstuhl für Informatik VI (Künstliche Intelligenz und Wissenssysteme)
• 依托单位国家: 德国
• 项目类别: Research data and software (Scientific Library Services and Information Systems)
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2019-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/394329162?language=en
• 关键词: Development; semi; automatic; open; source

The goal of the proposal is the further development of our efficient, semi-automatic and easy-to-use open-source segmentation tool LAREX und its integration in the open source workflow of the OCR-D functional model. The preliminary work LAREX (Layout Analysis and Region EXtraction) allows both a coarse segmentation by separation of text and non-text and a fine segmentation by detection and classification of different textual entites. LAREX utilizes an efficient implementation of the connected component approach. It has been used in the digitalization of different early prints und enables a qualitative good page segmentation with significantly less time than conventional alternatives. The main goal of the further development of LAREX is to reduce the degree of manual work. Therefore, a more robust segmentation und a further development of the rule and constraint language are necessary. The basic configurations should be easily adaptable to the peculiarities of a particular early print by both the users and learning algorithms. Furthermore, the comfortable GUI of LAREX for correction of single segmentation errors should be improved. This component is also necessary for defining a ground truth for learning algorithms and for evaluation. The overall goal is to find an optimal combination between manual and automatic methods. The tool and the process model will be substantially evaluated with various cooperation partners, in particular in the context of the digitalization of early prints within the OCR-D function model including the subsequent OCR by the linkage of external tools.

该提案的目标是进一步开发我们的高效，半自动和易于使用的开源分割工具LAREX及其集成在开源工作流程的OCR-D功能模型。初步工作LAREX（布局分析和区域提取）允许通过分离文本和非文本进行粗分割，通过检测和分类不同的文本实体进行细分割。LAREX利用连接组件方法的有效实现。它已被用于不同的早期印刷品的数字化，并能够以比传统替代品更少的时间实现质量良好的页面分割。LAREX进一步发展的主要目标是减少手工工作的程度。因此，一个更强大的分割和进一步发展的规则和约束语言是必要的。基本配置应该容易地适应用户和学习算法的特定早期打印的特性。此外，LAREX用于校正单个分割错误的舒适的GUI应得到改进。这个组件对于定义学习算法和评估的基础事实也是必要的。总体目标是找到手动和自动方法之间的最佳组合。将与各种合作伙伴一起对工具和流程模型进行实质性评估，特别是在OCR-D功能模型内的早期印刷品数字化的背景下，包括随后通过外部工具链接的OCR。