期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2014
卷号：7
期号：1
页码：169-180
DOI：10.14257/ijsip.2014.7.1.16
出版社：SERSC
摘要：A method based on local contour distribution features is proposed for writer identification in this paper. In preprocessing, contours are abstracted form images by an improved Bernson algorithm. Then the Local Contour Distribution Feature (LCDF) is extracted from the fragments which are parts of the contour in sliding windows. In order to reduce the impact of stroke weight, the fragments which do not directly connect the center point are ignored in the feature abstraction procedure. The edge point distributions of the fragments are counted and normalized into LCDFs. At last, the weighted Manhattan distance is used as similarity measurement. The experiments on our database and ICDAR 2011 writer identification database show that the performance of the proposed method reach or exceed those of existing state-of-art methods.
关键词：writer identification; stroke feature; local contour distribution feature; weighted ; Manhattan distance
