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A Fast Level Set-Like Algorithm with Topology Preserving Constraint

机译:具有拓扑约束的快速水平集样算法

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Implicit active contours are widely employed in image processing and related areas. Their implementation using the level set framework brings several advantages over parametric snakes. In particular, a parametrization independence, topological flexibility, and straightforward extension into higher dimensions have led to their popularity. However, in some applications the topological flexibility of the implicit contour is not desirable. Imposing topology-preserving constraints on evolving contours is often more convenient than including additional postprocessing steps. In this paper, we build on the work by Han et al. [1] introducing a topology-preserving extension of the narrow band algorithm involving simple point concept from digital geometry. In order to significantly increase computational speed, we integrate a fast level set-like algorithm by Nilsson and Heyden [2] with the simple point concept to obtain a fast topology-preserving algorithm for implicit active contours. The potential of the new algorithm is demonstrated on both synthetic and real image data.
机译:隐式活动轮廓线广泛应用于图像处理和相关领域。它们使用级别集框架的实现带来了比参数蛇更多的优势。特别地,参数化独立性,拓扑灵活性以及直接扩展到更高维度已导致它们的流行。但是,在某些应用中,隐式轮廓的拓扑灵活性是不希望的。在不断变化的轮廓上施加拓扑保留约束通常比包括其他后处理步骤更方便。在本文中,我们以Han等人的工作为基础。 [1]引入了窄带算法的拓扑保留扩展,其中涉及数字几何中的简单点概念。为了显着提高计算速度,我们将Nilsson和Heyden [2]提出的一种类似快速集的算法与简单点概念进行集成,以获得隐式活动轮廓的一种快速拓扑保留算法。在合成图像数据和真实图像数据上都证明了新算法的潜力。

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