Arbitrary-Oriented Scene Text Detection via Rotation Proposals

This paper introduces a novel rotation-based framework for arbitrary-oriented text detection in natural scene images. We present the Rotation Region Proposal Networks , which are designed to generate inclined proposals with text orientation angle information. The angle information is then adapted fo...

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Vydané v:IEEE transactions on multimedia Ročník 20; číslo 11; s. 3111 - 3122
Hlavní autori: Ma, Jianqi, Shao, Weiyuan, Ye, Hao, Wang, Li, Wang, Hong, Zheng, Yingbin, Xue, Xiangyang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
arbitrary oriented
Computer architecture
Computing time
Feature maps
Image detection
Image edge detection
Microsoft Windows
Pipelines
Proposals
Robustness
Rotation
rotation proposals
Scene text detection
Task analysis
ISSN:1520-9210, 1941-0077
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Shrnutí:This paper introduces a novel rotation-based framework for arbitrary-oriented text detection in natural scene images. We present the Rotation Region Proposal Networks , which are designed to generate inclined proposals with text orientation angle information. The angle information is then adapted for bounding box regression to make the proposals more accurately fit into the text region in terms of the orientation. The Rotation Region-of-Interest pooling layer is proposed to project arbitrary-oriented proposals to a feature map for a text region classifier. The whole framework is built upon a region-proposal-based architecture, which ensures the computational efficiency of the arbitrary-oriented text detection compared with previous text detection systems. We conduct experiments using the rotation-based framework on three real-world scene text detection datasets and demonstrate its superiority in terms of effectiveness and efficiency over previous approaches.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1520-9210
1941-0077
DOI:10.1109/TMM.2018.2818020