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Caption location and extraction in digital video based on SVM

机译:基于SVM的数字视频中的标题位置和提取

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Text that appears in a scene or graphically added to video can provide an important supplemental source of index information as well as clues for decoding the video's structure and for classification, and we call them closed caption. In this work, a novel algorithm is presented for detecting and locating caption in digital video. The first module of the system divides an image into small blocks featured by pixel value that is fed to SVM (support vector machine) to classify whether they are text blocks or not. The other module is to do post-processing on the classified text blocks to identify the rectangle region of them and OCR can be used further and easily. Experiments conducted with a variety of video sources show that our method could detect and locate caption region successfully by SVM with comparatively less samples.
机译:出现在场景中或以图形添加到视频中的文本可以提供一个重要的索引信息源以及解码视频结构和分类的线索,并且我们称之为隐藏标题。在这项工作中,提出了一种用于检测和定位数字视频中的标题的新颖算法。系统的第一个模块将图像划分为由像素值中的小块送到SVM(支持向量机)以分类它们是否是文本块。另一个模块是对分类文本块进行后处理以识别它们的矩形区域,并且可以进一步且容易地使用OCR。用各种视频来源进行的实验表明,我们的方法可以通过SVM与相对较少的样品成功地检测和定位字幕区域。

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