一种基于灰度值矩阵的文档复原方法研究  

Study of document recovery method based on gray-level matrix

作　　者：刘宪国[1] 贾子钰 刘万军[1] 韩敏[3] Liu Xianguo Jia Ziyu Liu Wanjun Han Min(School of Software, Liaoning Technical University, Huludao Liaoning 125105, China Beifing Key Laboratory of Traffic Data Analysis ＆ Mining, School of Computer ＆ Information Technology, Beijing Jiaotong University, Beijing 100044, China School of Control Science ＆ Engineering, Dalian University of Technology, Dalian Liaoning 116024, China)

机构地区：[1]辽宁工程技术大学软件学院,辽宁葫芦岛125105 [2]北京交通大学计算机与信息技术学院交通数据分析与挖掘北京市重点实验室,北京100044 [3]大连理工大学控制科学与工程学院,辽宁大连116024

出　　处：《计算机应用研究》2016年第12期3901-3904,3908,共5页Application Research of Computers

基　　金：辽宁省教育厅基金资助项目(L2012113)

摘　　要：对于切碎英文文档自动拼接还原中无法利用碎纸片几何形状特征的问题,提出一种基于灰度值矩阵的文档碎片拼接方法。利用碎片图像的特征向量消除同行字母处于不同高度的负影响,提取其特征位置作为动态聚类的分类标准,依据文本行特征进行动态聚类和类间排序,设计了一种基于原图像碎片边界矩阵的四邻拼接算法进行逐一高效地拼接还原。仿真结果表明,该方法准确率较高且操作简便,对规则碎片拼接还原具有良好的实际意义。Considering the lack of shape character in reconstruction of cross-cut English documents, this paper proposed an automatic reconstruction method of document fragment based on gray-level matrix. The method used eigenvectors of fragmented images to eliminat the negative effects of peer letters at different heights, extracted its features location as a dynamic clustering feature classification criteria, which provided text line characteristics for dynamic clustering and category sorting. This paper designed a neighborhood image stitching algorithm based on fragments of the original boundary matrix, one by one efficient remodeling. Simulation results show that the method has a high degree of accuracy and is convenient to operate. It has good practical significance for rule fragments mosaics restored.

关 键 词：文档碎片拼接 二值图像 特征位置 动态聚类 四邻拼接算法 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]