Text Detection in Nature Scene Images Using Two-stage Nontext Filtering

被引：0

作者：

Wang, Qingqing ^{[1
]}

Lu, Yue ^{[1
]}

Sun, Shiliang ^{[1
]}

机构：

[1] East China Normal Univ, Dept Comp Sci & Technol, Shanghai Key Lab Multidimens Informat Proc, Shanghai 200241, Peoples R China

来源：

2015 13TH IAPR INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR) | 2015年

关键词：

text detection; MSERs; CRF; nontext filtering; random forests; edge-cut;

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：

We present a text detection method in natural scene images based on two-stage nontext filtering. Firstly, we detect multi-channel maximally stable extremal regions (MSERs) as character candidates. To reduce the amount of repeating components, we merge the MSERs by choosing the most character-like ones when overlap happens. Then nontext components are filtered out by a two-stage labeling procedure, wherein we combine random forests with CRF. Finally, components labeled as text are grouped into words by an edge-cut strategy, and false positives are eliminated by a HOG-based classifier. The experimental results on the ICDAR2013 database show the effectiveness of the proposed method.

引用

页码：106 / 110

页数：5

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