Solving jigsaw puzzles by computer
Annals of Operations Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
Using visualization in the archaeological excavations of a pre-Inca temple in Peru
Proceedings of the 7th conference on Visualization '96
A Multiscale Method for the Reassembly of Two-Dimensional Fragmented Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching of 3-D curves using semi-differential invariants
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Techniques to Enhance Images for Mokkan Interpretation
ICFHR '10 Proceedings of the 2010 12th International Conference on Frontiers in Handwriting Recognition
Contour-shape based reconstruction of fragmented, 1600 BC wallpaintings
IEEE Transactions on Signal Processing
DAS '12 Proceedings of the 2012 10th IAPR International Workshop on Document Analysis Systems
A texture based approach to reconstruction of archaeological finds
VAST'05 Proceedings of the 6th International conference on Virtual Reality, Archaeology and Intelligent Cultural Heritage
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Historical documents are invaluable to study the society and culture in old ages everywhere in the world. In Japan, unearthed wooden tablets called Mokkan excavated from ancient palace sites and so on in the Nara period provide important clues to know the era. Since most of unearthed Mokkan have been badly damaged and broken into several pieces, however, it is extremely difficult even for experts to extract characters on fragmented Mokkan. In this paper, we propose a digital image reassembling scheme for fragmented Mokkan so that broken character images are reassembled and written content is analyzed. The proposed scheme consists of two steps: an image grouping using color features and an image reassembling using local tangent and curvature functions of the fragment contours. After the grouping process, fragment images with the same color features are clustered. Then, in the reassembling step, candidate matching pairs for adjacent fragment images in the same group are listed. We also provide a user interface for archeologists to verify the results. As a result, the system helps archaeologists reconstruct Mokkan images so that they can decode them.