Evaluation of shadow features
Evaluation of shadow features
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DOI：
10.1049/iet-cvi.2017.0159
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发表时间：
2018-02
期刊：
影响因子：
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通讯作者：
Liangqiong Qu;Jiandong Tian;Huijie Fan;Wentao Li;Yandong Tang
中科院分区：
文献类型：
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作者：
Liangqiong Qu;Jiandong Tian;Huijie Fan;Wentao Li;Yandong Tang
阴影特征，如颜色比例，纹理和色度已被证明是非常有效的阴影检测。基于阴影的不同特征，提出了许多阴影检测方法。然而，以往的阴影检测工作主要集中在现有的阴影特征设计一个有效的分类器，而很少关注的阴影特征本身的分析。大多数研究只是简单地报告最终的阴影检测结果，而不是对每个特征进行评估。读者通常不知道哪些特征更有效，或者这些阴影特征是否是互补的。以下问题仍未解决：每个特征的鲁棒性、哪个特征在检测方法中发挥最重要的作用、当前特征可以达到的最佳性能是多少。本研究的目的就是为了回答这些问题，并希望通过对常用阴影特征的评价，为未来的阴影检测算法提供指导。在一个大型数据集上进行了广泛的比较实验后，得到了一些有用和有趣的结论。
Shadow features such as colour ratio, texture, and chromaticity have proved to be quite effective in shadow detection. Many shadow detection methods have been proposed on the basis of different features. However, previous works for shadow detection mainly focus on designing an effective classifier for existing shadow features, but pay less attention on the analysis of shadow features themselves. The majority of studies simply report the final shadow detection results rather than make an evaluation on each feature. Readers often do not know which features are more effective or whether these shadow features are complementary. The following problems are still unsolved: the robustness of each feature, which feature plays the most important role in a detection method, and what is the best performance that current features can reach. The purpose of this study is to answer these questions, and the authors hope that this study can offer guidance for future shadow detection algorithms via the evaluation of frequently used shadow features. Several useful and interesting conclusions are obtained after conducting extensive comparison experiments on a large dataset.