一种新的运动目标轮廓检测方法

Yankun Wei, Wael Badawy
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引用次数: 7

摘要

提出了一种新的运动目标轮廓检测方法。该方法结合了静止图像分割和运动图像分割技术,提高了物体轮廓的处理速度和精度。该方法使用的运动分割算法是分层自适应结构网格(HASM),该算法提取运动目标的运动边界并去除噪声区域。然后在运动边界内检测前景像素点,并应用形态学运算生成前景斑点。采用简单的边缘检测技术得到运动物体的连续轮廓。这两种技术的结合降低了传统轮廓提取方法的整体计算成本,有效地提取了运动目标轮廓
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new moving object contour detection approach
A new moving object contour detection approach is proposed in this paper. This approach combines still image segmentation and motion segmentation techniques together to provide fast processing speed and accuracy of object contour. The motion segmentation algorithm used in the proposed approach is the hierarchical adaptive structured mesh (HASM), which extracts the motion boundary of the moving objects and removes noise regions. Then inside the motion boundary, the foreground pixels are detected and the morphological operations are applied to produce foreground blobs. Simple edge detection technique is used to get the continue contour of the moving object. The combination of these two techniques reduces the whole computational cost of traditional contour extraction approaches and efficiently extracts the moving object contour
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