针对智能视频监控中运动阴影影响目标跟踪和识别准确性的问题, 提出了一种基于颜色和梯度直方图反投影的阴影检测算法。以视觉背景提取模型检测得到的运动目标区域为基础, 首先在HSI颜色空间利用亮度和色度信息筛选出阴影像素, 然后通过梯度直方图反投影的方法区分运动目标和阴影, 最后将上述两种方法的检测结果进行合理融合得到最终的阴影检测区域。与典型算法的对比实验结果表明, 所提算法有效提高了阴影检测的准确性和鲁棒性, 适用于运动目标的实时检测和识别。

Considering that the accuracy of target tracking and recognition is disturbed by the moving shadow in intelligent video surveillance, we proposed a shadow detection algorithm based on color and gradient histogram back-projection. On the basis of the moving object region detected by visual background extractor model, the shadow pixels were screened by the intensity and chromaticity in HSI color space at first. Then, the gradient histogram back-projection method was used to distinguish the moving object from the shadow. Finally, the detection results based on the above two methods were reasonably fused to get the final shadow area. The experimental results show that: Compared with the typical algorithms, the proposed method can effectively improve the accuracy and robustness of shadow detection. Therefore, it can be applied in accurate moving object detection and recognition.