分割连接蛇形提取多目标边界算法的实验分析

Guo Cui, JaeYong Hwang, Jong-Whan Jang
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引用次数: 0

摘要

分割连接Snake提取多目标边界的最著名算法是利用Snake点之间的距离进行最接近的方法。由于对象拓扑的原因,它经常不能分割和连接Snake。本文对该问题进行了实验探讨。为了对具有复杂拓扑结构的Snake进行分割和连接,提出了利用Snake段之间向量的新算法。通过3个和5个目标的两幅测试图像的实验表明,本文提出的图像比最接近的图像效果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experimental Analysis of Algorithms of Splitting and Connecting Snake for Extracting of the Boundary of Multiple Objects
The most famous algorithm of splitting and connecting Snake for extracting the boundary of multiple objects is the nearest method using the distance between snake points. It often can`t split and connect Snake due to object topology. In this paper, its problem was discussed experimentally. The new algorithm using vector between Snake segment is proposed in order to split and connect Snake with complicated topology of objects. It is shown by experiment of two test images with 3 and 5 objects that the proposed one works better than the nearest one.
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