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This work deals with processing historical cadastral maps. It is part of a complex system for seamless map creation. The main goal is to detect and recognize so-called nomenclatures, text information composed of several components that specify the position of a map sheet in the coordinate system. This information will then be used to create a large seamless map, allowing for better online presentation. The main contribution of this work is the utilization of a modern end-to-end approach and its comparison with the currently used two-step approach combining text detection and OCR techniques. We chose a visual document understanding model, concretely Donut, for our experiments. The results prove that such models can be successfully trained for our task and outperform the traditional methods.

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Historical Map Understanding Using End-to-End Methods

  • 会议论文

  • 发表日期：

    2026年

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  • Ladislav Lenc,
  • Jiří Martínek,
  • Pavel Král

摘要

This work deals with processing historical cadastral maps. It is part of a complex system for seamless map creation. The main goal is to detect and recognize so-called nomenclatures, text information composed of several components that specify the position of a map sheet in the coordinate system. This information will then be used to create a large seamless map, allowing for better online presentation. The main contribution of this work is the utilization of a modern end-to-end approach and its comparison with the currently used two-step approach combining text detection and OCR techniques. We chose a visual document understanding model, concretely Donut, for our experiments. The results prove that such models can be successfully trained for our task and outperform the traditional methods.