第十二章:基于圆增广旋转轨迹算法的轮廓校正与分析

Russel A. Apu, M. Gavrilova
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引用次数: 1

摘要

提出了一种新的圆形增广旋转轨迹(CART)算法来计算基于r空间的形状描述子,从而实现了有效的形状匹配、泛化和分类。旋转不变的r空间表示可以用来检测不变的几何特征,尽管存在相当大的噪声和量化误差。此外,CART方法具有保角性,可以检测到噪声轨迹中的不连续点。实验分析表明,CART方法可以正确地检测和表示物体的固有形状,并提取其几何属性。该方法的通用性、鲁棒性和对各种复杂形状的一致性使其成为一种有效的轮廓表示和分析技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chapter 12: Contour Rectification and Analysis Using Circular Augmented Rotational Trajectory Algorithm
This paper presents a novel circular augmented rotational trajectory (CART) algorithm to compute an R-space based shape descriptors which allow efficient shape matching, generalization and classification. The rotation invariant R-space representation can be used to detect invariant geometric features despite the presence of considerable noise and quantization errors. Moreover, the CART method is corner preserving and can detect the points of discontinuity in a noisy trajectory. Experimental analysis performed on a number of difficult or ambiguous object boundaries show that the CART method can correctly detect and represent the inherent shape and extract their geometric properties. The method's universality, robustness and consistent performance on a variety of difficult shapes make it a power technique for contour representation and analysis.
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