Writer Identification Using Edge Based Features

被引：0

作者：

Fan, Zhenyin ^{[1
]}

Guo, Zhenhua ^{[2
]}

Chen, Youbin ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Wuhan, Peoples R China

[2] Tsinghua Univ, Grad Sch Shenzhen, Shenzhen, Peoples R China

来源：

PROCEEDINGS 3RD IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION ACPR 2015 | 2015年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we present a new method for writer identification, which extract original Local Binary Pattern(LBP) of different radius and Edge descriptors from the edge points of the handwriting. Then, we make combinations of these edge based features. Experimental results demonstrate that the combination of edge points based features outperform traditional features extracted from the whole text, which can get state-of-the-art performance on CVL and ICDAR2013 datasets.

引用

页码：416 / 420

页数：5

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