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A subpixel edge detection algorithm based on the combination of border following and gray moment

机译:基于边界跟随和灰度矩组合的亚像素边缘检测算法

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Subpixel edge detection is critical in three-dimension computer-assisted intra-operative navigation based on a marker-based matching technique, because it significantly influences the accuracy of guidance. In order to increase the accuracy, a gray moment based method is proposed to extract the accurate contours of the connected areas. Firstly, a border following algorithm is used to acquire a rough contour, and then the gradient at each point on the contour is obtained. The accurate contour is figured out subsequently by the gray moment along the gradient direction. To evaluate the accuracy of the proposed method, by using the output of a binocular vision system with a high-precision 3D spatial positioning device as the exact value, we compare results of the proposed method with those of several traditional methods. It turns out that the proposed method improves spatial positioning accuracy by an order of magnitude (i.e. from 1 mm to 0.1 mm). Finally, we show the potential of our approach as a general purpose contour detector which can be applied to tissue segmentation.
机译:亚像素边缘检测在基于标记的匹配技术的三维计算机辅助术中导航中至关重要,因为它会显着影响导航的准确性。为了提高精度,提出了一种基于灰度矩的方法来提取连接区域的准确轮廓。首先,使用边界跟踪算法获取粗糙轮廓,然后获得轮廓上每个点的梯度。随后通过沿梯度方向的灰色力矩确定出正确的轮廓。为了评估所提出方法的准确性,通过使用具有高精度3D空间定位设备的双目视觉系统的输出作为精确值,我们将所提出方法的结果与几种传统方法的结果进行了比较。事实证明,所提出的方法将空间定位精度提高了一个数量级(即,从1毫米到0.1毫米)。最后,我们展示了我们的方法作为通用轮廓检测​​器的潜力,可以将其应用于组织分割。

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