基于离散人工蜂群算法的文本片段恢复方法

Zeyuan Tao, Wanshuai Hu, Zijian Shan, Zixiao Pan
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摘要

本文提出了一种基于离散人工蜂群算法的文本片段恢复方法。首先,根据文本片段中字符的分布,对文本片段进行逐行聚类。随后,以每一行废纸边缘信息的匹配程度作为衡量碎片是否左右相邻的指标。建立了具有整体匹配度的最优恢复模型。最后,本文采用离散ABC算法对该问题进行求解。实验结果表明,该算法在文本片段恢复中具有良好的稳定性、高效性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Text fragment recovery method based on discrete artificial bee colony algorithm
This paper proposes a new method based on discrete artificial bee colony algorithm to solve the problem of text fragment recovery. First, text fragments are clustered by row according to the distribution of the characters in the fragments. Subsequently, the matching degree of the edge information of each row of scrap paper is used as an index to measure whether the debris is adjacent to the left and right. An optimal restoration model with an overall matching degree is established. Finally, this paper uses discrete ABC algorithm to solve the problem. The experimental results show that the algorithm has good stability, efficiency and robustness in the restoration of text fragments.
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