Combining Local Features For Offline Writer Identification

被引：26

作者：

Jain, Rajiv ^{[1
]}

Doermann, David ^{[1
]}

机构：

[1] Univ Maryland, Lab Language & Multimedia Proc, College Pk, MD USA

来源：

2014 14TH INTERNATIONAL CONFERENCE ON FRONTIERS IN HANDWRITING RECOGNITION (ICFHR) | 2014年

关键词：

Writer identification; Feature Combination; Handwriting;

D O I：

10.1109/ICFHR.2014.103

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Several powerful approaches have recently been proposed for writer identification, which rely on local descriptors that capture the texture, shape and curvature properties of the handwriting. In this paper we use combinations of three of these features (K-Adjacent Segments, SURF, and Contour Gradient Descriptors), to address the writer identification problem. Experiments demonstrate that feature combinations outperform individual features, resulting in state-of-the-art performance on three datasets.

引用

页码：583 / 588

页数：6

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