Topology-Aware Neural Vectorization of Orienteering Maps: Contour Segmentation as a Demanding Test Case for Editable Reconstruction

Borbás, Péter, Troll, Ede (2026) Topology-Aware Neural Vectorization of Orienteering Maps: Contour Segmentation as a Demanding Test Case for Editable Reconstruction In: Proceedings of the 13th International Conference on Applied Informatics. Eger, Eszterházy Károly Catholic University Líceum Publisher. pp. 66-80.

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Hivatalos webcím (URL): https://doi.org/10.17048/icai.2026.66

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We present a reproducible end-to-end pipeline for converting printed orienteering maps into editable vector layers. While the broader framework targets multiple ISOM symbol classes, this paper focuses on elevation contours as a particularly demanding test case because they are central to terrain interpretation, frequently occluded by overprinted symbols, and sensitive to topological degradation during raster-to-vector conversion. To assess practical usefulness rather than raster similarity alone, we combine overlap metrics (Dice, IoU, Boundary-F1) with topology- and structureaware measures, including Betti error, warping error, and graph-level error proxies. The experiments reveal a consistent raster–vector mismatch: models with nearly identical raster validation scores can produce materially different vector graphs after tracing. In particular, U-Net with a ResNet-18 encoder provided the best efficiency–quality trade-off despite near-tied raster scores with heavier variants, while topology-aware losses improved topologyrelated raster metrics without a comparably strong advantage in the postvectorization evaluation. These results show that editable map reconstruction must be evaluated end-to-end in the vector domain, since raster overlap alone is not a reliable proxy for downstream structural fidelity or subsequent editing effort.

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Borbás, Péter
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Troll, Ede
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Megjegyzés: This research was supported by the EKÖP-25-I-1 scholarship program.
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Kulcsszavak: orienteering maps, map vectorization, contour extraction, U-Net, topology-aware evaluation, raster-to-vector conversion
Nyelv: angol
DOI azonosító: 10.17048/icai.2026.66
Felhasználó: Tibor Gál
Dátum: 22 Szep 2026 06:50
Utolsó módosítás: 22 Szep 2026 06:50
URI: http://publikacio.uni-eszterhazy.hu/id/eprint/9436
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