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一种基于学习的视频字幕验证方法

DOI: 10.11834/jig.2006011283

Keywords: 视频字幕,字幕验证,2维主成分分析,支撑向量机

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Abstract:

视频字幕验证是字幕检测中的重要环节,其目的在于提高检测准确率。当前的验证方法多是依据经验规则。这些方法在图像背景复杂、图像分辨率低以及字幕字体、大小、颜色多变这些条件下,适应性差。为提高验证方法的适应性和准确性,通过将2维主成分分析(2DPCA)应用到视频字幕验证中,提出了一种基于2DPCA和支撑向量机(SVM)的视频字幕验证方法。该方法分训练和判别两个步骤,即首先采用2DPCA方法提取视频图像块特征,然后通过训练SVM对图像块进行验证和分类。实验结果表明.在图像背景复杂、图像分辨率低以及字幕字体、大小、颜色多变这些传统验证方法或多或少都存在困难的条件下,该方法不仅具有良好的视频字幕验证能力,而且也能明显降低算法的运行耗时。

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