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.
| Original language | English |
|---|---|
| Journal | Pattern Recognition Letters |
| Volume | 29 |
| Issue number | 14 |
| Pages (from-to) | 1924-1939 |
| Number of pages | 10 |
| ISSN | 0167-8655 |
| DOIs | |
| Publication status | Published - 2008 |
Keywords
- Faculty of Science
- Jigsaw puzzle solver
- Edge matching
- Piece classification
- Border similarity measure
- Co-occurrence matrix