基于分层聚类的仅横纵切碎中文纸片拼接分类

根据仅知道碎纸机横纵切破碎中文纸片的文字之间存在统一的文字高度和行间距等文字特征，提出在匹配拼接前，把碎纸片的二维图像通过横向投影方式转变为保留文字高度、行间距等特征的一维向量，并利用它进行分层聚类，对所有碎纸片进行行分类，从而有效地减少匹配拼接的时间，提高匹配拼接正确性，实验结果表明，该方法精确，有效。

The stitching classification of simple horizontally or vertically shredded Chinese papers based on hierarchical clustering

Due to the Chinese characters’ features of unified text height and line spacing, the 2D images of the scraps of simply horizontally or vertically shredded Chinese paper were converted into 1D vectors with the text height and line spacing via horizontal projection method. The paper shredders were differentiated in lines and classified based on hierarchical clustering to reduce the time of the stitching and to improve the accuracy of the stitching. The experimental results show that the method is accurate and effective.