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基于笔画相关加权的视频图像文字识别

             

摘要

In order to extract the subtitle in the video image, a robust method was proposed. First, the image edge feature was adopted in caption location step, and the binarization method of text images with the edge information was given. Then, the method combined with projection and regional generation was used to locate a character. Finally, taking fully account of the topology of the text strokes, the stroke correlation among the adjacent sub-grids was determined and the stroke fuzzy membership was used to complete the elastic grid feature extraction. This method can effectively get the binary image of characters from a complex background image, ensure the stability and robustness in feature extraction. The experimental results show the method is effective, and its recognition rate has been up to 92.1%.%为了提取影视视频图像中的字幕信息,提出一套鲁棒的方法:首先采用图像的边缘特征对字幕信息进行区域定位,并给出结合边缘信息的方法对图像文字进行二值化;其次,采用投影法和区域生成方法定位单个文字;最后,充分考虑到文字笔画的拓扑结构,进行相邻子网格笔画结构相关性的判定,并采用笔画模糊隶属度完成弹性网格特征的提取.该方法在复杂的背景图像中能够有效得到文字的二值图像,并保证了提取特征的稳定性、健壮性,对二值化后的影视字幕的识别率达到92.1%,实验结果表明了方法的有效性.

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