基于曲线拟合和细分的平面通用图像轮廓捕获方法

A. Ebrahimi, G. B. Loghmani, M. Sarfraz
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引用次数: 3

摘要

在本文中,设计了一种新技术,可以使用三次B´ezier曲线捕捉二维形状的轮廓。该方法避免了传统的全局平方拟合误差优化方法,强调数据点的局部控制。确定了最大误差以保证绝对拟合误差小于一个准则,并控制曲线细分过程。该方法根据给定的最大误差对复杂线段进行细分,同时进行曲线拟合。实验结果的对比研究表明,该方法具有表示准确、近似误差小、计算复杂度高等优点。
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Capturing Outlines of Planar Generic Images by Simultaneous Curve Fitting and Sub-division
In this paper, a new technique has been designed to capture the outline of 2D shapes using cubic B´ezier curves. The proposed technique avoids the traditional method of optimizing the global squared fitting error and emphasizes the local control of data points. A maximum error has been determined to preserve the absolute fitting error less than a criterion and it administers the process of curve subdivision. Depending on the specified maximum error, the proposed technique itself subdivides complex segments, and curve fitting is done simultaneously. A comparative study of experimental results embosses various advantages of the proposed technique such as accurate representation, low approximation errors and efficient computational complexity.
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