A High-Accuracy SSIM-based Scoring System for Coin Die Link Identification
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866912217238077440 |
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| author | Labedan, Patrice Drougard, Nicolas Berezin, Alexandre Sun, Guowei Dieulafait, Francis |
| author_facet | Labedan, Patrice Drougard, Nicolas Berezin, Alexandre Sun, Guowei Dieulafait, Francis |
| contents | The analyses of ancient coins, and especially the identification of those struck with the same die, provides invaluable information for archaeologists and historians. Nowadays, these die links are identified manually, which makes the process laborious, if not impossible when big treasures are discovered as the number of comparisons is too large. This study introduces advances that promise to streamline and enhance archaeological coin analysis. Our contributions include: 1) First publicly accessible labeled dataset of coin pictures (329 images) for die link detection, facilitating method benchmarking; 2) Novel SSIM-based scoring method for rapid and accurate discrimination of coin pairs, outperforming current techniques used in this research field; 3) Evaluation of clustering techniques using our score, demonstrating near-perfect die link identification. We provide datasets, to foster future research and the development of even more powerful tools for archaeology, and more particularly for numismatics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_01186 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A High-Accuracy SSIM-based Scoring System for Coin Die Link Identification Labedan, Patrice Drougard, Nicolas Berezin, Alexandre Sun, Guowei Dieulafait, Francis Computer Vision and Pattern Recognition The analyses of ancient coins, and especially the identification of those struck with the same die, provides invaluable information for archaeologists and historians. Nowadays, these die links are identified manually, which makes the process laborious, if not impossible when big treasures are discovered as the number of comparisons is too large. This study introduces advances that promise to streamline and enhance archaeological coin analysis. Our contributions include: 1) First publicly accessible labeled dataset of coin pictures (329 images) for die link detection, facilitating method benchmarking; 2) Novel SSIM-based scoring method for rapid and accurate discrimination of coin pairs, outperforming current techniques used in this research field; 3) Evaluation of clustering techniques using our score, demonstrating near-perfect die link identification. We provide datasets, to foster future research and the development of even more powerful tools for archaeology, and more particularly for numismatics. |
| title | A High-Accuracy SSIM-based Scoring System for Coin Die Link Identification |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2502.01186 |