期刊
IEEE TRANSACTIONS ON MULTIMEDIA
卷 20, 期 11, 页码 3111-3122出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMM.2018.2818020
关键词
Scene text detection; arbitrary oriented; rotation proposals
资金
- National Key R&D Program of China [2017YFC0803700]
- National Natural Science Foundation of China [61602459, 61572138, U1611461]
- Science and Technology Commission of Shanghai Municipality [17511101902, 16JC1420400]
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.
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