基于显著性检测的电视角标自适应阈值分割算法

Xinwei Wang, Dongmei Li, Shaobin Li, Yuzhen Sun, Shanzhen Lan
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引用次数: 1

摘要

电视角标广泛应用于当前的视频节目中,成为信息提取与分析的热点之一。电视角标检测与分割算法是信息提取的重要内容。本文提出了一种基于时间平均边缘检测和显著性检测相结合的自适应阈值分割算法,从视频序列中有效地分离和提取电视角标。首先应用Canny算子检测边缘,然后计算10帧的加权平均边缘,得到时间平均边缘图像。然后将时间平均边缘图像与显著性图相结合,得到更精确的分割结果。最后,采用自适应阈值分割算法对角标进行分割。实验结果表明,该方法可以有效地检测和分离角标与背景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TV Corner-Logo Adaptive Threshold Segmentation Algorithm Based on Saliency Detection
TV corner-logo is widely used in current video program, and becomes one of the hot spots in information extraction and analysis. TV corner-logo detection and segmentation algorithm is important for information extraction. In this paper, we presented an adaptive threshold segmentation algorithm, based on the combined time-averaged edge detection and saliency detection, to effectively separate and extract the TV corner-logo from the video sequence. First, we applied Canny operator to detect edges and then calculate the weighted average edge of ten frames, so as to get the time-averaged edge image. Then we combine the time-averaged edge image with the saliency map to get a more accurate segmentation. Finally, we used the adaptive threshold segmentation algorithm to separate the corner-logo. Experimental results show that, this method can effectively detect and separate the corner-logo from the background.
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