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Reassembling Shredded Document Stripes Using Word-Path Metric and Greedy Composition Optimal Matching Solver

机译:使用Word-Path度量和贪婪构成最佳匹配求解器重新组装切碎的文档条纹

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This paper develops a shredded document reassembly algorithm based on character/word detection. A new word compatibility estimation metric and a searching strategy called Greedy Composition and Optimal Matching (GCOM) are proposed to compose documents from their vertically shredded stripes. We reduce the stripe puzzle reassembly problem to the traveling salesman problem (TSP) on a sparse graph. The word-path compatibility metric takes advantages of the optical character recognition (OCR) to compute the compatibility score among a group of stripes. The global composition strategy, based on an integration of greedy composition and optimal matching, is proposed to search for a maximal Hamiltonian path and the final global reassembly. We demonstrate that our solver outperforms the state-of-the-art puzzle solvers on reassembling stripe shredded documents.
机译:本文开发了一种基于字符/字检测的切碎文件重组算法。提出了一种新的单词兼容性估计度量和名为贪婪组成和最佳匹配(GCOM)的搜索策略,以从垂直切碎的条纹构成文档。在稀疏图表中,我们将条纹拼写重新组装出现问题(TSP)。单词路径兼容性度量可利用光学字符识别(OCR)来计算一组条纹之间的兼容性得分。基于贪婪组成和最佳匹配的整合,全球构成策略是为了寻找最大哈密顿路径和最终全球重组。我们展示了我们的求解器优于最先进的拼写求解器在重新组装条纹碎片的文件上。

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