Solving jigsaw puzzles using image features

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Solving jigsaw puzzles using image features. / Nielsen, Ture R.; Drewsen, Peter; Hansen, Klaus.

In: Pattern Recognition Letters, Vol. 29, No. 14, 2008, p. 1924-1939.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Nielsen, TR, Drewsen, P & Hansen, K 2008, 'Solving jigsaw puzzles using image features', Pattern Recognition Letters, vol. 29, no. 14, pp. 1924-1939. https://doi.org/10.1016/j.patrec.2008.05.027

APA

Nielsen, T. R., Drewsen, P., & Hansen, K. (2008). Solving jigsaw puzzles using image features. Pattern Recognition Letters, 29(14), 1924-1939. https://doi.org/10.1016/j.patrec.2008.05.027

Vancouver

Nielsen TR, Drewsen P, Hansen K. Solving jigsaw puzzles using image features. Pattern Recognition Letters. 2008;29(14):1924-1939. https://doi.org/10.1016/j.patrec.2008.05.027

Author

Nielsen, Ture R. ; Drewsen, Peter ; Hansen, Klaus. / Solving jigsaw puzzles using image features. In: Pattern Recognition Letters. 2008 ; Vol. 29, No. 14. pp. 1924-1939.

Bibtex

@article{4c843e508a1e11dd9c20000ea68e967b,
title = "Solving jigsaw puzzles using image features",
abstract = "In this article, we describe a method for automatic solving of the jigsaw puzzle problem based on using image features instead of the shape of the pieces. The image features are used for obtaining an accurate measure for edge similarity to be used in a new edge matching algorithm. The algorithm is used in a general puzzle solving method which is based on a greedy algorithm previously proved successful. We have been able to solve computer generated puzzles of 320 pieces as well as a real puzzle of 54 pieces by exclusively using image information.Additionally, we investigate a new scalable algorithm which exploits the divide and conquer paradigm to reduce the combinatorially complex problem by classifying the puzzle pieces and comparing pieces drawn from the same group. The paper includes a brief preliminary investigation of some image features used in the classification.",
keywords = "Faculty of Science, Jigsaw puzzle solver, Edge matching, Piece classification, Border similarity measure, Co-occurrence matrix",
author = "Nielsen, {Ture R.} and Peter Drewsen and Klaus Hansen",
year = "2008",
doi = "10.1016/j.patrec.2008.05.027",
language = "English",
volume = "29",
pages = "1924--1939",
journal = "Pattern Recognition Letters",
issn = "0167-8655",
publisher = "Elsevier BV * North-Holland",
number = "14",

}

RIS

TY - JOUR

T1 - Solving jigsaw puzzles using image features

AU - Nielsen, Ture R.

AU - Drewsen, Peter

AU - Hansen, Klaus

PY - 2008

Y1 - 2008

N2 - In this article, we describe a method for automatic solving of the jigsaw puzzle problem based on using image features instead of the shape of the pieces. The image features are used for obtaining an accurate measure for edge similarity to be used in a new edge matching algorithm. The algorithm is used in a general puzzle solving method which is based on a greedy algorithm previously proved successful. We have been able to solve computer generated puzzles of 320 pieces as well as a real puzzle of 54 pieces by exclusively using image information.Additionally, we investigate a new scalable algorithm which exploits the divide and conquer paradigm to reduce the combinatorially complex problem by classifying the puzzle pieces and comparing pieces drawn from the same group. The paper includes a brief preliminary investigation of some image features used in the classification.

AB - In this article, we describe a method for automatic solving of the jigsaw puzzle problem based on using image features instead of the shape of the pieces. The image features are used for obtaining an accurate measure for edge similarity to be used in a new edge matching algorithm. The algorithm is used in a general puzzle solving method which is based on a greedy algorithm previously proved successful. We have been able to solve computer generated puzzles of 320 pieces as well as a real puzzle of 54 pieces by exclusively using image information.Additionally, we investigate a new scalable algorithm which exploits the divide and conquer paradigm to reduce the combinatorially complex problem by classifying the puzzle pieces and comparing pieces drawn from the same group. The paper includes a brief preliminary investigation of some image features used in the classification.

KW - Faculty of Science

KW - Jigsaw puzzle solver

KW - Edge matching

KW - Piece classification

KW - Border similarity measure

KW - Co-occurrence matrix

U2 - 10.1016/j.patrec.2008.05.027

DO - 10.1016/j.patrec.2008.05.027

M3 - Journal article

VL - 29

SP - 1924

EP - 1939

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

SN - 0167-8655

IS - 14

ER -

ID: 6223142