Regularized Laplacian zero crossings as optimal edge integrators
Regularized Laplacian zero crossings as optimal edge integrators
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DOI：
10.1023/a:1023030907417
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发表时间：
2003-07-01
影响因子：
19.5
通讯作者：
Bruckstein, AM
中科院分区：
文献类型：
--
作者：
Kimmel, R;Bruckstein, AM
我们在几何变分框架中查看对象分割的基本边缘集成问题。首先，我们表明，Marr 和 Hildreth 提出的图像拉普拉斯边缘检测器的经典零交叉本质上提供了关于非常自然的几何函数的最佳边缘积分。该函数累积边缘法线与沿边缘的灰度级图像梯度之间的内积。我们利用这一观察结果，基于该函数并通过先前提出的测地线活动轮廓几何变分模型进行正则化，得出新的高精度活动轮廓。我们还将 Haralick 边缘检测器的 2D 几何变分解释纳入几何活动轮廓框架中。
We view the fundamental edge integration problem for object segmentation in a geometric variational framework. First we show that the classical zero-crossings of the image Laplacian edge detector as suggested by Marr and Hildreth, inherently provides optimal edge-integration with regard to a very natural geometric functional. This functional accumulates the inner product between the normal to the edge and the gray level image-gradient along the edge. We use this observation to derive new and highly accurate active contours based on this functional and regularized by previously proposed geodesic active contour geometric variational models. We also incorporate a 2D geometric variational explanation to the Haralick edge detector into the geometric active contour framework.