基于序列图像的运动目标检测

Moving object detection based on image sequences

  • 摘要: 针对动态环境下运动目标检测中噪声多、目标检测不完整等情况,提出了一种基于金字塔多分辨率模型的运动目标检测方法,在低分辨率下获取目标的区域,在高分辨率下获取目标的细节。对于复杂的环境,还提出了运用高低双阈值替代传统的单阈值进行图像差分运算的方案,阈值可以根据图像自动分析得到。该方法首先将当前帧和背景帧进行尺度变换,得到不同分辨率下的图像组,然后在不同尺度下得到高低阈值差分图像,最后从高层向低层进行有效融合,得到噪声少的完整目标图像。实验表明,该方法提取运动目标的精度比较高,单目标达到0.802,多目标达到0.615,尤其是在复杂的动态环境下,优势比较明显。

     

    Abstract: According to the problems of numerous noises and incomplete detection of moving object in dynamic environments, a method for moving target detection based on pyramid-style multi-resolution model was proposed. The areas of target were obtained in low resolution and the details were in high resolution. For complex environment, an image difference operation scheme using high/low double-threshold substituted for traditional single threshold was proposed, which could obtain thresholds automatically. The scale transformation of the current and background frames was carried out first and a group of images in different resolutions were obtained. Then the high/low threshold differential images in different scale spaces were got. At last, an image fusion process was done from the high layer to the low layer, and an integrated object image with few noises was obtained. Experimental results show that the proposed method achieves a high accuracy for the moving object extraction, it has obvious advantages especially in complex dynamic environment. The precision is 0.802 for single object and 0.615 for multi object.

     

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