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作 者:邢楠 张建奇[1] 刘鹏飞 曹芙蓉 XING Nan;ZHANG Jianqi;LIU Pengfei;CAO Furong(School of Physics and Optoelectronic Engineering,Xidian Univ.,Xi’an 710071,China;School of Automation and Information Engineering,Xi’an Univ.of Technology,Xi’an 710048,China)
机构地区:[1]西安电子科技大学物理与光电工程学院,陕西西安710071 [2]西安理工大学自动化与信息工程学院,陕西西安710048
出 处:《西安电子科技大学学报》2018年第4期34-39,共6页Journal of Xidian University
基 金:国家自然科学基金资助项目(61575152;61705179)
摘 要:针对被碎纸机破碎的纸质文件难以复原的问题,提出一种新颖的破碎文件重构方法.首先根据中文字符的结构特点,建立字符在碎片中的结构块模型,并通过分类器对结构块加以识别;然后利用结构块之间的匹配概率以及不匹配数量,对碎片的匹配程度进行度量;进而将两种匹配度量加以融合,生成用于碎片全局匹配的评价函数;最后以评价函数为判定依据,通过遗传算法实现碎片的最佳匹配.实验结果表明,该方法能有效抑制信息缺损等对文件重构的影响,相比于已有方法,它具有较高的重构准确率.To solve the problem that it is difficult to recover the paper document destroyed by a shredder,a novel method for destroyed document reconstruction is proposed.First,based on the structural characteristics of Chinese words,the structural block model of the character in shred is built,and the structural blocks are identified by a classifier.Second,the matching degrees between shreds are measured by the matching probability and the number of mismatches between structural blocks.Third,the two matching measures are fused to generate an evaluation function for the global matching of shreds.Finally,based on the evaluation function,the best matching of shreds is realized by the genetic algorithm.Experimental results show that the proposed method can effectively restrain the effect of information loss,etc.on the document reconstruction,and that it achieves a higher reconstruction accuracy than the existing methods.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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