Text detection in natural scene images with user-intention

Liuan Wang, Wei-liang Fan, Yuan He, Jun Sun, Yutaka Katsuyama, Y. Hotta
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引用次数: 5

Abstract

We propose an accurate and robust coarse-to-fine text detection scheme with user-intention which captures the intrinsic characteristics of natural scene texts. In the coarse detection stage, a double edge detector is designed to estimate the symmetry of stroke and the stroke width, which help segment the foreground. Then the initial user-intention region is extended to generate a coarse bounding box based on the estimated foreground. In the refinement stage, candidate connected components (CCs) from Niblack decomposition, are grouped together by location to form text lines after noise removal and layer selection. Experimental results demonstrate the effectiveness of the proposed method which yields higher performance compared with state-of-the-art methods.
具有用户意图的自然场景图像文本检测
提出了一种具有用户意图的精确、鲁棒的粗到精文本检测方案,该方案能够捕捉自然场景文本的内在特征。在粗检测阶段,设计了双边缘检测器来估计笔画的对称性和笔画宽度,从而对前景进行分割。然后对初始用户意图区域进行扩展,生成基于估计前景的粗边界框。在细化阶段,从Niblack分解得到的候选连通分量(CCs),经过去噪和层选择后,按位置分组形成文本行。实验结果证明了该方法的有效性,与现有方法相比具有更高的性能。
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