Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China.
Department of Information & Communication Engineering, Nanjing Institute of Technology, Nanjing 211167, China.
Comput Intell Neurosci. 2020 Jan 9;2020:2075781. doi: 10.1155/2020/2075781. eCollection 2020.
Shadow detection and removal in real scene images are a significant problem for target detection. This work proposes an improved shadow detection and removal algorithm for urban video surveillance. First, the foreground is detected by background subtraction and the shadow is detected by HSV color space. Using local variance and OTSU method, we obtain the moving targets with texture features. According to the characteristics of shadow in HSV space and texture feature, the shadow is detected and removed to eliminate the shadow interference for the subsequent processing of moving targets. Finally, we embed our algorithm into C/S framework based on the HTML5 web socket protocol. Both the experimental and actual operation results show that the proposed algorithm is efficient and robust in target detection and shadow detection and removal under different scenes.
实景图像中的阴影检测和去除是目标检测的一个重大问题。本工作提出了一种改进的城市视频监控中的阴影检测和去除算法。首先，通过背景减除法检测前景，通过 HSV 颜色空间检测阴影。利用局部方差和 OTSU 方法，获得具有纹理特征的运动目标。根据 HSV 空间和纹理特征中的阴影特点，检测并去除阴影，以消除阴影对后续运动目标处理的干扰。最后，我们将算法嵌入到基于 HTML5 网络套接字协议的 C/S 框架中。实验和实际运行结果表明，该算法在不同场景下的目标检测和阴影检测及去除中具有高效性和鲁棒性。
