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A New Method for Arbitrarily-Oriented Text Detection in Video

机译:一种新的视频中任意化文本检测方法

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Text detection in video frames plays a vital role in enhancing the performance of information extraction systems because the text in video frames helps in indexing and retrieving video efficiently and accurately. This paper presents a new method for arbitrarily-oriented text detection in video, based on dominant text pixel selection, text representatives and region growing. The method uses gradient pixel direction and magnitude corresponding to Sobel edge pixels of the input frame to obtain dominant text pixels. Edge components in the Sobel edge map corresponding to dominant text pixels are then extracted and we call them text representatives. We eliminate broken segments of each text representatives to get candidate text representatives. Then the perimeter of candidate text representatives grows along the text direction in the Sobel edge map to group the neighboring text components which we call word patches. The word patches are used for finding the direction of text lines and then the word patches are expanded in the same direction in the Sobel edge map to group the neighboring word patches and to restore missing text information. This results in extraction of arbitrarily-oriented text from the video frame. To evaluate the method, we considered arbitrarily-oriented data, non-horizontal data, horizontal data, Hua's data and ICDAR-2003 competition data (Camera images). The experimental results show that the proposed method outperforms the existing method in terms of recall and f-measure.
机译:视频帧中的文本检测在增强信息提取系统的性能方面起着至关重要的作用,因为视频帧中的文本有助于有效准确地索引和检索视频。本文基于主导文本像素选择,文本代表和地区生长,介绍了视频中任意导向文本检测的新方法。该方法使用与输入帧的Sobel边缘像素对应的梯度像素方向和幅度,以获得优势文本像素。然后提取与主导文本像素相对应的Sobel边缘映射中的边缘组件,我们称之为文本代表。我们消除了每个文本代表的破碎细分,以获得候选人的文本代表。然后候选文本代表的周边沿着Sobel边缘映射中的文本方向增长,以对我们称之为Word修补程序的相邻文本组件。单词修补程序用于查找文本行的方向,然后单词修补程序在Sobel边缘映射中的相同方向展开,以对邻近的文字修补程序进行分组并恢复丢失的文本信息。这导致从视频帧提取取向任意导向的文本。为了评估方法,我们考虑了任意导向的数据,非水平数据,水平数据,华氏数据和ICDAR-2003竞争数据(相机图像)。实验结果表明,该方法在召回和F测量方面优于现有方法。

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