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Gradient Vector Flow Snake with Embedded Edge Confidence

机译:具有嵌入式边缘置信度的梯度矢量流蛇

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摘要

Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly in locating object boundaries. Problems associated with initialization and poor convergence to boundary concavities have limited their utility. Gradient vector flow (GVF) snake solved both problems successfully. However, boundaries in noisy images are often blurred even destroyed with smoothing and false results usually occur when such images are processed even with GVF snake model. We have incorporated embedded edge confidence (EEC) into GVF snake model. The improved method can solve this problem when noisy images were processed.
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,特别是在定位对象边界时。与初始化和边界凹面收敛性差相关的问题限制了它们的实用性。梯度矢量流(GVF)蛇成功解决了这两个问题。但是,即使使用GVF蛇模型处理噪声图像,嘈杂图像中的边界也经常模糊甚至被平滑破坏,并且通常会出现错误结果。我们已将嵌入式边缘置信度(EEC)合并到GVF蛇模型中。改进的方法可以解决噪声图像处理时的问题。

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