多封闭轮廓分割的亲和矩阵性质

Kanglin Xu, G. Luger
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引用次数: 0

摘要

本文描述了一种基于沿布朗运动方向运动的粒子所跟踪的轮廓分布的分割算法。从数学的角度分析了以边到边转移概率为元素的关联矩阵的性质,并给出了形式化证明。这种分析是必不可少的,因为我们可以使用亲和矩阵的属性来大大减少在解决分割问题时的计算量,特别是对于大的真实图像。所得到的结果可用于机器人视觉伺服在场景中挑选多个目标
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Properties of the affinity matrix for multiple closed contour segmentation
In this paper, we describe an algorithm based on a distribution of contours traced by particle moving in directions undergoing Brownian motion for a segmentation problem. We analyze the properties of the affinity matrix, whose elements are the edge-to-edge transition probabilities, from a mathematical point of view and give formal proofs. This analysis is essential because we can use the properties of the affinity matrix to reduce the amount of computation greatly when solving segmentation problems, especially for large real images. The results obtained can be used for robot visual servo to pick multiple objects in the scene
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