中文摘要：

针对网络视频中模糊变化，以及镂空、透明台标的背景变化都易造成台标区域内容变化，导致现有台标识别算法效率降低的问题，提出一种针对网络视频的鲁棒的台标识别方法．为了应对多种台标变化，提出一种基于Gabor滤波器组的近似不变特征的鲁棒台标特征；建立了一种由拟合特征簇表面获得的若干超椭球组成的台标判定模型，用计算高维空间点和超椭球位置关系取代复杂的分类算法，且可以只利用单帧信息进行台标识别，显著地提高了判定速度．实验结果表明，该方法较好地解决了台标识别中模糊变化、镂空和透明台标背景变化下的识别问题，能够高效识别各种台标，在单帧条件下平均F1统计变量达97．3％．

英文摘要：

Recognizing TV logo in internet videos is a very challenge task, because the logo region is vulnerable to blurring and background changes dramatically especially for the hollow-out or semitransparent logos. Aimed at solving these problems, a Gabor filter bank-based approximate invariant feature is proposed to construct robust logo features against blurring and background changes. A new logo matching model is built on some certain fitted ellipsoids of the feature cluster＇s surfaces, so that complex classification may be replaced by simple determining the position relationship between logo feature and ellipsoids, which can dramatically speed up logo matching and enable TV logo recognition with one single frame. Experiments show that tb, e proposed method can efficiently recognize all kinds of logos and achieves 97. 3% F1 measurement on average.