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Farsi/Arabic text extraction from video images by corner detection

机译:通过角点检测从视频图像中提取波斯语/阿拉伯语文本

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Video text information plays an important role in semantic-based video analysis, indexing and retrieval. In this paper, we proposed a novel Farsi text detection approach based on intrinsic characteristics of Farsi text lines, which is more robust to complex backgrounds and various font styles. First, by an edge detector operator, all the possible edges in vertical, horizontal, 45 and 135 degrees are extracted. Then, for extracting text strokes, some pre-processing such as dilation and erosion are done according to the font size. Afterward, by finding the edges cross points, corners map is extracted. To discard non-text corners and finding real font size, histogram analysis is done. After finding real font size, input image is rescaled and a new corner map is extracted. Finally, the detected candidate text areas undergo the empirical rules analysis to identify text areas and project profile analysis for verification and text lines extraction. Experimental results demonstrate that the proposed method is robust to font size, font colour, and background complexity.
机译:视频文本信息在基于语义的视频分析,索引和检索中起着重要作用。在本文中,我们提出了一种基于波斯语文本行内在特征的新颖波斯语文本检测方法,该方法对于复杂的背景和各种字体样式都更加健壮。首先,由边缘检测器操作员提取垂直,水平,45度和135度的所有可能边缘。然后,为了提取文本笔划,根据字体大小进行一些预处理,例如膨胀和腐蚀。然后,通过找到边缘的交叉点,提取角点图。为了丢弃非文本角并找到实际的字体大小,可以进行直方图分析。找到实际的字体大小后,将重新缩放输入图像的比例,并提取一个新的角图。最后,对检测到的候选文本区域进行经验规则分析,以识别文本区域并进行项目配置文件分析,以进行验证和文本行提取。实验结果表明,该方法对字体大小,字体颜色和背景复杂度具有鲁棒性。

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