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Snakes, shapes, and gradient vector flow

机译:蛇,形状和梯度矢量流

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Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to boundary concavities, however, have limited their utility. This paper presents a new external force for active contours, largely solving both problems. This external force, which we call gradient vector flow (GVF), is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. It differs fundamentally from traditional snake external forces in that it cannot be written as the negative gradient of a potential function, and the corresponding snake is formulated directly from a force balance condition rather than a variational formulation. Using several two-dimensional (2-D) examples and one three-dimensional (3-D) example, we show that GVF has a large capture range and is able to move snakes into boundary concavities.
机译:蛇或活动轮廓在计算机视觉和图像处理应用中被广泛使用,特别是用于定位对象边界。但是,与初始化相关的问题以及边界凹面收敛性差,限制了它们的实用性。本文提出了一种主动轮廓的新外力,在很大程度上解决了这两个问题。我们将此外力(我们称为梯度矢量流(GVF))计算为从图像得出的灰度或二进制边缘图的梯度矢量的扩散。它与传统的蛇形外力从根本上不同之处在于,它不能写成势函数的负梯度,并且相应的蛇形是直接根据力平衡条件而不是变式来表示的。通过使用几个二维(2-D)示例和一个三维(3-D)示例,我们显示GVF具有较大的捕获范围,并且能够将蛇移动到边界凹面中。

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