Abstract
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.
Highlights
Shadow elimination process is widely used as a preprocessing operation in various video surveillance applications, such as environmental monitoring [1], motion detection [2], and security monitoring [3,4,5]
We present a novel shadow elimination algorithm based on HSV and texture features to overcome the disadvantages of the traditional HSV color space model in the web video analysis application
In order to improve the accuracy of motion detection, this paper proposes the improved shadow elimination algorithm based on the C/S framework of HTML5. e basic structure diagram is shown in Figure 4. e test video is processed through the proposed shadowing algorithm on the server and the final result is displayed on the client
Summary
Shadow elimination process is widely used as a preprocessing operation in various video surveillance applications, such as environmental monitoring [1], motion detection [2], and security monitoring [3,4,5]. It can eliminate the undesirable effect of noise on the performance of such systems. Many methods have been proposed based on color models [7], region [8, 9], learning [10], and invariant image models [11, 12]. The shadow is detected by the HSV color space which includes the information of the hue, the saturation, and the brightness. e discriminating function of the shadow detection is
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