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Playfield extraction in soccer video based on Lab color space classification

机译:基于Lab颜色空间分类的足球视频运动场提取

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The growing growth of soccer videos and its enormous popularity around the world has caused the need of creating an automated analysis system. Recognition and extraction of playfield is considered as one of the most basic processes in the analysis of soccer video. Playfield extraction is developed to identify important parts of the shot and remove other additional parts as well as reducing the processing space in order to increase system speed. This paper presents a framework based on Lab color space for classification and extraction playfield in a soccer video. In this method, first, the image is converted to the Lab color space, then the resulting image is classified in order to separate the playfield from other parts. Finally, by using morphological operations, errors and noises are removed and the playfield is extracted as a convex-hull. Experimental results showed that the proposed method is performing very well in the Lab color space, even in the difficult light conditions such as shadows.
机译:足球视频的增长和在世界范围内的广泛普及,导致需要创建一个自动分析系统。运动场的识别和提取被认为是足球视频分析中最基本的过程之一。游戏场提取的开发旨在识别镜头的重要部分,并删除其他附加部分,并减少处理空间,以提高系统速度。本文提出了一种基于Lab色彩空间的框架,用于足球视频中的运动场分类和提取。在这种方法中,首先,将图像转换为Lab颜色空间,然后对所得图像进行分类,以将运动场与其他部分分开。最后,通过形态学运算,消除了错误和噪声,并将运动场提取为凸包。实验结果表明,即使在困难的光照条件下(例如阴影),该方法在Lab色彩空间中的表现也非常好。

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