Text Search: Towards Fast Text Localization in Scene Images

被引：0

作者：

Yang, Lei ^{[1
]}

Cheng, Samuel ^{[1
]}

Verma, Pramode K. ^{[1
]}

Wang, Shuang ^{[2
]}

机构：

[1] Univ Oklahoma, Dept Elect & Comp Engn, Tulsa, OK 74135 USA

[2] Univ Calif San Diego, Dept Biomed Informat, San Diego, CA 92103 USA

来源：

PROCEEDINGS OF 2016 IEEE INTERNATIONAL SYMPOSIUM ON MULTIMEDIA (ISM) | 2016年

关键词：

text localization; ConvNet; region proposals;

D O I：

10.1109/ISM.2016.135

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 an efficient approach to text localization. We restrict our attention to the text localization and refer to our method as 'text search'. In particular, we pre-trained a text detection ConvNet which skip the region proposal process, and integrates bounding boxes and text confidence score into the output layer. Our approach achieved similar high precision with [1], and acceptable level of recall.

引用

页码：83 / 86

页数：4

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