Arbitrary-Oriented Scene Text Detection via Rotation Proposals
Arbitrary-Oriented Scene Text Detection via Rotation Proposals
复制标题
通过旋转建议进行任意方向的场景文本检测
DOI：
10.1109/tmm.2018.2818020
复制
发表时间：
2018-11-01
影响因子：
7.3
通讯作者：
Xue, Xiangyang
中科院分区：
文献类型：
--
作者：
Ma, Jianqi;Shao, Weiyuan;Xue, Xiangyang
本文介绍了一种新的基于旋转的自然场景图像文本检测框架。我们提出了旋转区域提案网络，该网络被设计用于生成带有文本方向角度信息的倾斜提案。然后将角度信息用于边界框回归，使建议在方向上更准确地适合文本区域。提出了旋转兴趣区域池层，用于将任意方向的建议投影到文本区域分类器的特征映射中。整个框架建立在基于区域提议的体系结构上，与以往的文本检测系统相比，保证了面向任意方向的文本检测的计算效率。我们在三个真实场景文本检测数据集上使用基于旋转的框架进行了实验，并证明了其在有效性和效率方面优于先前的方法。
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.