Abstract
In intelligent video surveillance systems, the detected moving objects often contain shadows which may deteriorate the performance of object detections. Therefore, shadow detection and removal is an important step employed after foreground extraction. Since HSV color space gives a better separation of chromaticity and intensity, it has been commonly adopted to detect and remove shadow. However, almost all the HSV color space based methods use static thresholds to separate shadows from foreground. In this paper, a dynamic threshold based method is proposed. In the proposed approach, the threshold prediction model is first established by a statistical analysis tool and then the predicted dynamic thresholds are used for shadow detection. Experiments on a self-built dataset show that the proposed method can get better reliability and robustness than the traditional methods using static thresholds.
Highlights
In recent years, for the sake of public security, the Closed Circuit Television (CCTV) has been installed to many public places, such as school, department store, elevator and parking lot, etc
To get the illuminance value for research, we use the illuminance capture device for data collection, and we developed an Illuminance Input System (IIS) to collect illuminance value
According to the statistical results, we find that the FVp /BVp ratio will decrease along with the illuminance value increased
Summary
Current moving object detection approaches usually have a typical drawback: moving shadows tend to be classified as part of the foreground. Texture-based methods assume that shadow regions and background share the same texture structures [8]. It does not depend on colors, and would be robust to illumination changes. As Computer Science and Information Technology 3(3): 70-75, 2015 time goes by, the illuminance will change which results in different shadow description, so it’s hard to remove shadow correctly by the static thresholds. A new shadow removal method that can use dynamically the illuminance value is proposed to solve the above problem.
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