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Fast and robust text detection in images and video frames

机译:在图像和视频帧中进行快速可靠的文本检测

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Text in images and video frames carries important information for visual content understanding and retrieval. In this paper, by using multiscale wavelet features, we propose a novel coarse-to-fine algorithm that is able to locate text lines even under complex background. First, in the coarse detection, after the wavelet energy feature is calculated to locate all possible text pixels, a density-based region growing method is developed to connect these pixels into regions which are further separated into candidate text lines by structural information. Secondly, in the fine detection, with four kinds of texture features extracted to represent the texture pattern of a text line, a forward search algorithm is applied to select the most effective features. Finally, an SVM classifier is used to identify true text from the candidates based on the selected features. Experimental results show that this approach can fast and robustly detect text lines under various conditions.
机译:图像和视频帧中的文本承载着重要的信息,有助于视觉内容的理解和检索。在本文中,通过使用多尺度小波特征,我们提出了一种新的从粗到细算法​​,即使在复杂背景下也能够定位文本行。首先,在粗略检测中,在计算了小波能量特征以定位所有可能的文本像素之后,开发了基于密度的区域增长方法,以将这些像素连接到通过结构信息进一步分成候选文本行的区域。其次,在精细检测中,通过提取四种纹理特征来表示文本行的纹理图案,应用正向搜索算法选择最有效的特征。最后,SVM分类器用于根据所选功能从候选者中识别真实文本。实验结果表明,该方法可以在各种条件下快速,可靠地检测文本行。

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