Automatic color based reassembly of fragmented images and paintings
IEEE Transactions on Image Processing
Document analysis applied to fragments: feature set for the reconstruction of torn documents
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Multi-feature matching of fresco fragments
ACM SIGGRAPH Asia 2010 papers
Wavelet-based inpainting for object removal from image series
Proceedings of the 32nd DAGM conference on Pattern recognition
Recursive interlocking puzzles
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Global consistency in the automatic assembly of fragmented artefacts
VAST'11 Proceedings of the 12th International conference on Virtual Reality, Archaeology and Cultural Heritage
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The puzzle assembly problem has many application areas such as restoration and reconstruction of archeological findings, repairing of broken objects, solving jigsaw type puzzles, molecular docking problem, etc. The puzzle pieces usually include not only geometrical shape information but also visual information such as texture, color, and continuity of lines. This paper presents a new approach to the puzzle assembly problem that is based on using textural features and geometrical constraints. The texture of a band outside the border of pieces is predicted by inpainting and texture synthesis methods. Feature values are derived from these original and predicted images of pieces. An affinity measure of corresponding pieces is defined and alignment of the puzzle pieces is carried out using an FFT based image registration technique. The optimization of total affinity gives the best assembly of puzzle. Experimental results are presented on real and artificial data sets.