BullingerDB: A Dataset for Handwritten Text Recognition and Writer Retrieval

This dataset provides machine-readable and image-based resources from the Bullinger Digital project, a digital scholarly edition of the correspondence and writings related to the Swiss reformer Heinrich Bullinger (1504–1575). The collection aims to provide a final version of the correspondance ready to use as a benchmark dataset for tasks in the domain of historical document analysis. The handwriting consists of multiple languages - mostly Latin and Old German - but other languages such as Greek also occur. The release contains manuscript page images, line images including the transcription, metadata information (writer, year), and train/test splits for the task of handwritten text recognition and writer retrieval. The statistics for the two tasks proposed - handwritten text recognition and writer retrieval - are shown below. More statistics as well as information about how transcriptions were obtained can be found in our ICDAR2026 paper. Statistics for the task of handwritten text recognition Training Test Frequent Test Non-Frequent Writers 144 144 652 Letters 7,834 939 1,529 Pages 15,619 1,957 3,311 Lines 376,582 48,197 74,443 Statistics for the task of writer retrieval Training Test Writers 164 632 Letters 2,142 8,160 Pages 4,396 16,502 Downloadable files bullingerdb-pages.tar.gz High-resolution manuscript page facsimiles. bullingerdb-lines.tar.gz Cropped line images extracted from manuscript pages. bullingerdb-wr.tar.gzWriter Retrieval page split. The facsimiles are binarized. train.tsvTraining split for HTR. freq_test.tsvFrequent-writer test evaluation split. nonfreq_test.tsvNon-frequent-writer test evaluation split. letters.csvMetadata describing the writer and the year information for every letter. persons.csvMapping from writer ID to the actual person. Information for usage The collection consists of three different hierarchies: Letters, pages and lines. While the facsimile and the line images are sorted according to the letter (the directory 1-1000 contains the letters 1-1000, and each letter has its own directory and lists the pages for this letter), the writer retrieval split is split into a train and test split (WRITER-LETTER-PAGE.png). The meta information (writer and year information) is included in letters.csv. ├── bullingerdb-pages/│ ├── 1-1000/│ │ ├── 1/│ │ │ ├── 0001.png│ │ │ ├── 0002.png│ │ │ └── ...│ │ ├── 2/│ │ └── ...│ ├── 1001-2000/│ └── ... For example, 1-1000/1/0002.png refers to the second page of letter 1. ├── bullingerdb-lines/│ ├── 1-1000/│ │ ├── 1/│ │ │ ├── 0001_1.jpg│ │ │ ├── 0001_2.jpg│ │ │ ├── ... For example, 1/0001_2.jpg refers to the second line of the first page of letter 1. ├── bullingerdb-wr/│ ├── train/│ │ ├── 257_10959_0001.png│ │ ├── 260_11006_0001.png│ │ └── ...│ ├── test/│ │ ├── 6_4016_0001.png│ │ ├── 6_4016_0002.png│ │ └── ... For example, 6_4016_0001.png refers to the first page of letter 4016, written by p6 (see letters.csv). Potential use cases The dataset may be used for handwritten text recognition, writer identification and attribution, writer adaption of computation paleography in general. The benchmarks for HTR and writer identification are listed in the corresponding paper published at ICDAR 2026. Licensing and reuse If you use the dataset, we request you to include a citation to our ICDAR 2026 publication in which the resource is introduced. Additionally, the facsimiles (bullingerdb-pages) may be freely used for scientific, private, non-commercial, and commercial purposes provided the following information is included: the holding archive (Ort der Aufbewahrung) the corresponding archival signature (Signatur) a link to the Creative Commons Attribution-ShareAlike 4.0 International license: Creative Commons BY-SA 4.0 Whenever possible, please also reference the Bullinger Digital project: Bullinger Digital Project - You can also find further information about the Bullinger corpus there.本数据集源自布林格数字项目（Bullinger Digital），该项目是针对瑞士宗教改革家海因里希·布林格（Heinrich Bullinger，1504–1575）相关书信与著作的学术性数字校勘版本，提供可机读格式与基于图像的两类资源。本数据集旨在提供最终版书信语料，可作为历史文档分析领域相关任务的基准数据集使用。该手写文本涵盖多种语言，以拉丁语与古德语为主，同时也包含希腊语等其他语种。 本次发布的资源包含手稿页面图像、附带转录文本的行级图像、元数据信息（作者、创作年份），以及面向手写文本识别（Handwritten Text Recognition, HTR）与作者检索（Writer Retrieval）任务的训练/测试划分集。本次提出的两项任务的统计信息如下所示，更多统计数据以及转录文本的获取方式，请参阅我们发表于ICDAR 2026的论文。 #### 手写文本识别任务统计 | 划分类型 | 训练集 | 高频作者测试集 | 低频作者测试集 | |----------------|--------|----------------|----------------| | 作者数量 | 144 | 144 | 652 | | 书信总数 | 7,834 | 939 | 1,529 | | 手稿页面总数 | 15,619 | 1,957 | 3,311 | | 行级图像总数 | 376,582| 48,197 | 74,443 | #### 作者检索任务统计 | 划分类型 | 训练集 | 测试集 | |----------------|--------|--------| | 作者数量 | 164 | 632 | | 书信总数 | 2,142 | 8,160 | | 手稿页面总数 | 4,396 | 16,502 | ### 可下载文件 - `bullingerdb-pages.tar.gz`：高分辨率手稿页面影印件 - `bullingerdb-lines.tar.gz`：从手稿页面裁剪得到的行级图像 - `bullingerdb-wr.tar.gz`：用于作者检索任务的页面划分集，其影印图像已完成二值化处理 - `train.tsv`：手写文本识别任务的训练划分集 - `freq_test.tsv`：高频作者测试评估划分集 - `nonfreq_test.tsv`：低频作者测试评估划分集 - `letters.csv`：描述每封书信的作者与创作年份的元数据文件 - `persons.csv`：作者ID与真实姓名的映射表 ### 使用说明 本数据集包含三种层级结构：书信、页面与行级图像。其中影印图像与行级图像按照书信进行组织（`1-1000`目录包含编号1至1000的书信，每封书信拥有独立目录并存放对应书信的所有页面），而作者检索任务的划分集则分为训练与测试子集（命名格式为`WRITER-LETTER-PAGE.png`）。元数据信息（作者与创作年份）已包含在`letters.csv`文件中。 目录结构示例如下： ├── bullingerdb-pages/ │ ├── 1-1000/ │ │ ├── 1/ │ │ │ ├── 0001.png │ │ │ ├── 0002.png │ │ │ └── ... │ │ ├── 2/ │ │ └── ... │ ├── 1001-2000/ │ └── ... 例如，路径`1-1000/1/0002.png`指代第1封书信的第2页。 ├── bullingerdb-lines/ │ ├── 1-1000/ │ │ ├── 1/ │ │ │ ├── 0001_1.jpg │ │ │ ├── 0001_2.jpg │ │ │ ├── ... 例如，路径`1/0001_2.jpg`指代第1封书信第1页的第2行图像。 ├── bullingerdb-wr/ │ ├── train/ │ │ ├── 257_10959_0001.png │ │ ├── 260_11006_0001.png │ │ └── ... │ ├── test/ │ │ ├── 6_4016_0001.png │ │ ├── 6_4016_0002.png │ │ └── ... 例如，路径`6_4016_0001.png`指代由作者`p6`（详见`letters.csv`）创作的第4016封书信的第1页。 ### 潜在应用场景 本数据集可应用于手写文本识别、作者识别与归属判定，以及计算古文字学领域的作者适配等任务。手写文本识别与作者识别任务的基准测试结果已发表于ICDAR 2026的对应论文中。 ### 许可与复用规则 若您使用本数据集，请务必引用我们发表于ICDAR 2026的相关论文，该论文正式介绍了本数据集资源。 此外，若需使用影印图像资源（`bullingerdb-pages`），可在满足以下条件的前提下，将其用于科研、个人、非商业及商业用途： 1. 标注收藏档案机构（Ort der Aufbewahrung） 2. 标注对应档案编号（Signatur） 3. 附上知识共享署名-相同方式共享4.0国际许可协议（Creative Commons BY-SA 4.0）的链接 若条件允许，还请引用布林格数字项目（Bullinger Digital Project），您可在该项目官网获取布林格语料库的更多相关信息。