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首页> 外文期刊>Journal of mathematical imaging and vision >Geodesic Distance and Curves Through Isotropic and Anisotropic Heat Equations on Images and Surfaces
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Geodesic Distance and Curves Through Isotropic and Anisotropic Heat Equations on Images and Surfaces

机译:通过图像和表面上各向同性和各向异性热方程的测地距离和曲线

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This paper proposes a method to extract geodesic distance and geodesic curves using heat diffusion. The method is based on Varadhan's formula that helps to obtain a numerical approximation of geodesic distance according to metrics based on different heat flows. The heat equation can be utilized by regarding an image or a surface as a medium for heat diffusion and letting the user set at least one source point in the domain. Both isotropic and anisotropic diffusions are considered here to obtain geodesics according to their respective metrics. (1) In the part of the paper where we deal with the isotropic case, we use gray-level intensity to compute the conductivity, i.e., those pixels with gray-levels similar to the source point would have higher conductivity. The model of Perona and Malik, which inhibits heat from diffusing out of homogeneous regions, is also used for geodesic computations in this paper. The two methods are combined and used for more complicated cases. We can also use the norm of the gradient of an image as the feature in the Perona and Malik model to make the heat diffuse along boundaries and edges. (2) For the anisotropic case, we use different eigenvectors and eigenvalues to compose the diffusion tensors to concentrate heat flow along chosen directions. Furthermore, to automate the process of extracting geodesic lines, we propose two automatic methods: a new voting method and a key point method, which are both especially designed for the heat-based method. Our algorithms are tested on synthetic and real images as well as on a mesh. The results are very promising and demonstrate the robustness of the algorithms.
机译:提出了一种利用热扩散提取测地距离和测地曲线的方法。该方法基于Varadhan公式,该公式有助于根据基于不同热流的度量来获得测地线距离的数值近似值。通过将图像或表面视为热扩散的媒介,并让用户在域中设置至少一个源点,可以利用热方程。在这里考虑各向同性和各向异性扩散,以便根据它们各自的度量获得测地线。 (1)在本文处理各向同性情况的部分中,我们使用灰度强度来计算电导率,即,灰度级类似于源点的那些像素将具有更高的电导率。 Perona和Malik的模型还可以将热量抑制从同质区域扩散出去,该模型也用于测地学计算。两种方法结合起来,用于更复杂的情况。我们还可以将图像的梯度范数用作Perona和Malik模型的特征,以使热量沿边界和边缘扩散。 (2)对于各向异性的情况,我们使用不同的特征向量和特征值组成扩散张量,以沿选定方向集中热流。此外,为使测地线的提取过程自动化,我们提出了两种自动方法:新的投票方法和关键点方法,这两种方法都是专门为基于热量的方法设计的。我们的算法已在合成和真实图像以及网格上进行了测试。结果是非常有希望的,并证明了算法的鲁棒性。

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