首页> 外文会议>Pacific Rim International Conference on Artificial Intelligence(PRICAI 2006); 20060807-11; Guilin(CN) >Invariant Color Model-Based Shadow Removal in Traffic Image and a New Metric for Evaluating the Performance of Shadow Removal Methods
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Invariant Color Model-Based Shadow Removal in Traffic Image and a New Metric for Evaluating the Performance of Shadow Removal Methods

机译:基于不变颜色模型的交通图像阴影去除和评估阴影去除方法性能的新指标

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摘要

To track objects in a traffic image sequence, objects must be extracted first. Background differencing is frequently used to extract objects. When objects are extracted, it is quite possible that shadows are included. With shadow it is not easy to do precise tracking. Thus shadows need to be removed. To do this, we proposed invariant color-based shadow removal method. Many shadow removal methods were proposed. To compare the quality of methods, several metrics were suggested. However, they suffer from inconsistency where qualitative and quantitative results do not coincide. In this paper, we proposed a new metric having such consistency.
机译:要跟踪交通图像序列中的对象,必须首先提取对象。背景差异通常用于提取对象。提取对象时,很可能会包含阴影。对于阴影,进行精确跟踪并不容易。因此需要去除阴影。为此,我们提出了基于不变色的阴影去除方法。提出了许多阴影去除方法。为了比较方法的质量,建议了几个指标。但是,它们在定性和定量结果不一致的地方遭受不一致的困扰。在本文中,我们提出了一种具有这种一致性的新指标。

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