Optimization for automated assembly of puzzles

Warning The system is temporarily closed to updates for reporting purpose.

Sağıroğlu, Mahmut Şamil and Erçil, Aytül (2010) Optimization for automated assembly of puzzles. Top, 18 (2). pp. 321-338. ISSN 1134-5764 (Print) 1863-8279 (Online)

This is the latest version of this item.

[thumbnail of This is a RoMEO green publisher -- author can archive pre-print (ie pre-refereeing)] PDF (This is a RoMEO green publisher -- author can archive pre-print (ie pre-refereeing))
TOP.pdf

Download (1MB)

Abstract

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 formulated as an optimization problem where the optimum assembly of the pieces is achieved by maximizing the total affinity measure. An fft based image registration technique is used to speed up the alignment of the pieces. Experimental results are presented on real and artificial data sets.
Item Type: Article
Uncontrolled Keywords: Archeological reconstruction - Partial matching - Puzzle solving - Inpainting - Image registration
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: Aytül Erçil
Date Deposited: 20 Dec 2010 09:35
Last Modified: 26 Apr 2022 08:44
URI: https://research.sabanciuniv.edu/id/eprint/16177

Available Versions of this Item

Actions (login required)

View Item
View Item