12.3.1.2 Shredded Documents, Document Assembly

Chapter Contents (Back)
Matching, Regions. Matching, Contours. Shredded Documents. Not a lot of work, but an interesting subset.

Liu, H.R.[Hai-Rong], Cao, S.J.[Sheng-Jiao], Yan, S.C.[Shui-Cheng],
Automated Assembly of Shredded Pieces From Multiple Photos,
MultMed(13), No. 5, 2011, pp. 1154-1162.
IEEE DOI 1110
BibRef

Geller, T.[Tom],
DARPA Shredder Challenge Solved,
CACM(55), No. 8, August 2012, pp. 16-17.
DOI Link 1208
In the end some human help, but the crowdsourced version failed (to win, it did complete the task). A lot of automation used. BibRef

Richter, F., Ries, C.X., Cebron, N., Lienhart, R.,
Learning to Reassemble Shredded Documents,
MultMed(15), No. 3, 2013, pp. 582-593.
IEEE DOI 1303
BibRef

Andaló, F.A.[Fernanda A.], Taubin, G.[Gabriel], Goldenstein, S.[Siome],
PSQP: Puzzle Solving by Quadratic Programming,
PAMI(39), No. 2, February 2017, pp. 385-396.
IEEE DOI 1702
maximization of a constrained quadratic function. E.g. Shredded documents. BibRef

Le, C., Li, X.,
JigsawNet: Shredded Image Reassembly Using Convolutional Neural Network and Loop-Based Composition,
IP(28), No. 8, August 2019, pp. 4000-4015.
IEEE DOI 1907
graph theory, greedy algorithms, image classification, image matching, learning (artificial intelligence), neural nets, loop closure constraints BibRef

Liang, Y., Li, X.,
Reassembling Shredded Document Stripes Using Word-Path Metric and Greedy Composition Optimal Matching Solver,
MultMed(22), No. 5, May 2020, pp. 1168-1181.
IEEE DOI 2005
Measurement, Optical character recognition software, Optimal matching, Image reconstruction, global reconstruction from local alignments BibRef

Paixão, T.M.[Thiago M.], Berriel, R.F.[Rodrigo F.], Boeres, M.C.S.[Maria C.S.], Koerich, A.L.[Alessandro L.], Badue, C.[Claudine], de Souza, A.F.[Alberto F.], Oliveira-Santos, T.[Thiago],
Self-supervised deep reconstruction of mixed strip-shredded text documents,
PR(107), 2020, pp. 107535.
Elsevier DOI 2008
BibRef
And:
Fast(er) Reconstruction of Shredded Text Documents via Self-Supervised Deep Asymmetric Metric Learning,
CVPR20(14331-14339)
IEEE DOI 2008
Measurement, Mathematical model, Task analysis, Forensics, Manuals, Machine learning, Shape. Deep learning, Self-supervised learning, Fully convolutional neural networks, Document reconstruction, Optimization search BibRef

de Lima-Hernandez, R.[Roberto], Vergauwen, M.[Maarten],
A Generative and Entropy-Based Registration Approach for the Reassembly of Ancient Inscriptions,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Paixão, T.M.[Thiago M.], Berriel, R.F.[Rodrigo F.], Boeres, M.C.S.[Maria C.S.], Koerich, A.L.[Alessandro L.], Badue, C.[Claudine], de Souza, A.F.[Alberto F.], Oliveira-Santos, T.[Thiago],
A human-in-the-loop recommendation-based framework for reconstruction of mechanically shredded documents,
PRL(164), 2022, pp. 1-8.
Elsevier DOI 2212
Document reconstruction, Forensics, Jigsaw puzzle solving, Deep learning, Active learning BibRef


Chen, G.H.[Guang-Hao], Wu, J.[Jue], Jia, C.D.[Cun-Di], Zhang, Y.Z.[Yun-Zhou],
A pipeline for reconstructing cross-shredded English document,
ICIVC17(1034-1039)
IEEE DOI 1708
Fats, Gold, IP networks, cross-shredded document, hungarian algorithm, improved K-means algorithm, pipeline, reconstruction BibRef

Shang, S.Z.[Shi-Ze], Sencar, H.T.[Husrev T.], Memon, N.[Nasir], Kong, X.W.[Xiang-Wei],
A semi-automatic deshredding method based on curve matching,
ICIP14(5537-5541)
IEEE DOI 1502
Color BibRef

Saboia, P.[Priscila], Goldenstein, S.K.[Siome K.],
Assessing Cross-Cut Shredded Document Assembly,
CIARP14(272-279).
Springer DOI 1411
BibRef

Ranca, R.[Razvan], Murray, I.[Iain],
A Composable Strategy for Shredded Document Reconstruction,
CAIP13(II:324-331).
Springer DOI 1311
BibRef

Deever, A.[Aaron], Gallagher, A.[Andrew],
Semi-automatic assembly of real cross-cut shredded documents,
ICIP12(233-236).
IEEE DOI 1302
BibRef

Lin, H.Y.[Huei-Yung], Fan-Chiang, W.C.[Wen-Cheng],
Image-Based Techniques for Shredded Document Reconstruction,
PSIVT09(155-166).
Springer DOI 0901
BibRef

Ukovich, A., Ramponi, G.,
Features for the Reconstruction of Shredded Notebook Paper,
ICIP05(III: 93-96).
IEEE DOI 0512
BibRef

Biswas, A., Bhowmick, P.[Partha], Bhattacharya, B.B.[Bhargab B.],
Reconstruction of Torn Documents Using Contour Maps,
ICIP05(III: 517-520).
IEEE DOI 0512
BibRef

Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Matching, Affine Transformations .


Last update:Mar 25, 2024 at 16:07:51