中文摘要：

阴影给许多计算机视觉任务带来困难，例如图像分割、物体识别、边缘检测等。正确的阴影检测不但可以避免上述问题，同时也是阴影去除的基础。因此，阴影检测技术是图像处理和计算机视觉等相关领域的一个研究热点，近年来提出了大量算法。目前，关于视频中的动态阴影，在权威期刊已发表数篇综述性文献，但针对图像中的静态阴影，国内外尚未发表相关的评述性文献。本文对近年来提出的静态阴影检测算法按照基于模型的检测算法、基于本征图像的检测算法和基于统计学习的检测算法进行了分类和评述，总结了静态阴影检测的研究现状，分析了存在的问题并进行了展望。

英文摘要：

Shadows cause problems in many computer vision tasks,including image segmentation,object recogni-tion,and edge detection.Shadow detection can be used to avoid the above-mentioned problems and can aid in shadow removal.Therefore,shadow detection is a popular topic in both image processing and in computer vision.Many shadow detection algorithms have been proposed in recent years.Currently,several review arti-cles for moving shadow detection algorithms have been published;however,such a paper has not yet appeared for static shadow detection algorithms.In this study,we divide recent static shadow detection approaches into three categories：model-based methods,intrinsic image-based methods,and statistical learning-based meth-ods.We survey and summarize the current status of these areas of research.We also discuss the open prob-lems and future development.