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Extraction of text from videos based on layered method

机译：基于分层方法的视频提取文本

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The text data present in video contain certain useful information for automatic annotation, indexing, and structuring of images. However variations of the text due to complex background make the problem of automatic text extraction extremely difficult job. To address this problem a large number of techniques have been developed. Here a technique to extract text from video is proposed. Video can be considered as a sequence of frames. Identify a frame that contains text information. Take that particular frame as image. Then color clustering is used to divide images into multiple layers according to main color class. After that, obtain the candidate text regions from each color layer and determine whether the candidate text regions is real text regions in the corresponding image layer. The interference of the background can be effectively minimized, since the monochrome color exists in each layer, which can significantly increase the accuracy of text regions localization. After wards, an OCR package is used to recognize the text regions. Since the text region has only one color, it helps to greatly increase the recognition rate. Finally, the relationship between different layers is used to verify the recognition results by the text location.
机译：视频中存在的文本数据包含用于图像的自动注释，索引和结构的某些有用的信息。然而，由于复杂的背景，文本的变化使得自动文本提取的问题非常困难。为了解决这个问题，已经开发了大量技术。这里提出了一种从视频中提取文本的技术。视频可以被认为是一系列帧。确定包含文本信息的帧。将那个特定的帧作为图像。然后，颜色聚类用于根据主色类将图像分成多个层。之后，从每个颜色层获取候选文本区域，并确定候选文本区域是否是相应图像层中的真实文本区域。可以有效地最小化背景的干扰，因为每层中存在单色颜色，这可以显着提高文本区域定位的准确性。在病房之后，使用OCR包来识别文本区域。由于文本区域只有一种颜色，因此有助于大大提高识别率。最后，使用不同层之间的关系用于验证文本位置的识别结果。

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