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Solving jigsaw puzzles using image features

机译:使用图像特征解决拼图游戏

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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.
机译:在本文中,我们介绍一种基于图像特征而不是碎片形状的自动解决拼图难题的方法。图像特征用于获得边缘相似度的准确度量,以用于新的边缘匹配算法。该算法用于一般的难题求解方法,该方法基于先前证明是成功的贪心算法。我们已经能够完全通过使用图像信息来解决由计算机生成的320个拼图以及54个真实拼图的难题。此外,我们研究了一种新的可扩展算法,该算法利用分而治之范式通过对拼图碎片进行分类并比较从同一组中提取的碎片来减少组合复杂的问题。本文包括对分类中使用的某些图像特征的简要初步调查。

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