构建首个大规模古天文书图文字区域检测数据集，支持多语言与多风格分析。
Text region detection in historical astronomical diagrams
- 设计有序多边形标注方案，精准定位文字区域并记录阅读方向。
- 在10940个文字区域上验证模型，Poly-DETR达到新最佳性能。
- 适合历史文献数字化、跨语言图文分析研究者使用。
文本检测是历史文档分析的关键任务。尽管手稿和地图的文本检测已有数据集与基准，数学图表中的文本研究仍鲜受关注。为此，我们构建了一个大规模、多样化的开源数据集，包含948幅跨十个世纪（8至18世纪）的古天文书图，共10,940个有向多边形文字区域。数据覆盖阿拉伯语、波斯语（115）、汉语（332）、拜占庭语（233）、拉丁语（185）、希伯来语（48）和梵语（35）七种主要语言传统，涵盖符号到多行段落等丰富内容。每个文字实例均以有序多边形标注，精确界定区域并编码阅读方向。此外，对拉丁语图中2,293个区域标注了20类标签。我们在该数据集上评估了TESTR、DeepSolo++和Poly-DETR等基线模型，其中改进版DINO-DETR（Poly-DETR）表现最优，在MTHv2和cBAD2019基准上达到当前最佳水平。代码与数据集已公开。
原文摘要 · Abstract (English)
Text detection is a crucial task in the analysis of historical documents. While datasets and benchmarks exist for text detection in manuscripts and maps, the study of text in mathematical diagrams has received little attention. To address this, we introduce a large-scale, diverse, open-access dataset of 948 historical astronomical diagrams containing 10,940 oriented polygonal text regions. Our dataset spans ten centuries (8th to 18th) and seven main linguistic traditions: Arabic and Persian (115), Chinese (332), Byzantine (233), Latin (185), Hebrew (48), and Sanskrit (35). It captures a wide range of diagram styles and textual content, from symbols to multi-line paragraphs. Each text instance is annotated with ordered polygons that precisely delineate text regions and encode the reading direction. In addition, we annotated the 2,293 regions in Latin diagrams with 20 class labels. We evaluated several strong baselines on our dataset, including TESTR, DeepSolo++, and Poly-DETR, a simple extension of DINO-DETR that we design to predict ordered polygon vertices. Poly-DETR achieves state-of-the-art performance on the MTHv2 and cBAD2019 benchmarks and provides a solid, simple baseline on our dataset. Code and dataset available online.
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