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首页> 外文期刊>Journal of visual communication & image representation >Text detection and restoration in natural scene images
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Text detection and restoration in natural scene images

机译：自然场景图像中的文本检测和恢复

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摘要

A new method for text detection and recognition in natural scene images is presented in this paper. In the detection process, color, texture, and OCR statistic features are combined in a coarse-to-fine framework to discriminate texts from non-text patterns. In this approach, color feature is used to group text pixels into candidate text lines. Texture feature is used to capture the "dense intensity variance" property of text pattern. Statistic features from OCR (Optical Character Reader) results are employed to further reduce detection false alarms empirically. After the detection process, a restoration process is used. This process is based on plane-to-plane homography. It is carried out to refine the background plane of text when an affine transformation is detected on a located text and independent of camera parameters. Experimental results tested from a large dataset have demonstrated that the proposed method is effective and practical.
机译：本文提出了一种在自然场景图像中进行文本检测和识别的新方法。在检测过程中，将颜色，纹理和OCR统计信息特征组合到从粗到精的框架中，以区分文本与非文本模式。在这种方法中，颜色特征用于将文本像素分组为候选文本行。纹理特征用于捕获文本图案的“密集强度变化”属性。利用OCR（光学字符读取器）结果的统计功能，可以凭经验进一步减少检测错误警报。在检测过程之后，使用恢复过程。该过程基于平面到平面的单应性。当在所定位的文本上检测到仿射变换并且与相机参数无关时，执行此操作以完善文本的背景平面。从大型数据集测试的实验结果表明，该方法是有效且实用的。

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