Detection of depth and orientation discontinuities in range images using mathematical morphology

P. Boulanger, F. Blais, Philip R. Cohen
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引用次数: 18

Abstract

A technique for the detection of depth and orientation discontinuities in range images is described. This method uses basic morphological operators to extract these discontinuities from a dense range map. The authors describe how to extract depth discontinuities using the morphological edge operator of J.S.J. Lee et al. (1987) and how to use a top-hat operator to localize the exact positions of these discontinuities. The detection of orientation discontinuities is then discussed in detail. The calculation of a good estimate of the surface normals using anisotropic filtering inhibited at depth discontinuities is demonstrated. Once these estimates of the normals are calculated, operations similar to those used in depth discontinuity detection are used to locate orientation discontinuities at abrupt variations of the surface normals. Experimental results demonstrate computation of the positions of these discontinuities at pixel precision as well as very efficient use of morphological operators to localize abrupt variations in a noisy image signal in less than 1 s using a Datacube image processor.<>
用数学形态学检测距离图像的深度和方向不连续性
描述了一种检测距离图像中深度和方向不连续性的技术。该方法使用基本形态学算子从密集的距离图中提取这些不连续点。作者描述了如何使用J.S.J. Lee等人(1987)的形态学边缘算子提取深度不连续点,以及如何使用顶帽算子来定位这些不连续点的确切位置。然后详细讨论了定向不连续的检测。在深度不连续处,利用各向异性滤波可以很好地估计地表法线。一旦计算出这些法线的估计值,就可以使用与深度不连续检测类似的操作来定位地表法线突变处的方向不连续点。实验结果表明,使用Datacube图像处理器可以以像素精度计算这些不连续点的位置,并非常有效地使用形态学算子在不到1秒的时间内定位噪声图像信号中的突变变化。
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