基于线性规划和相似变换的点匹配算法

doi:10.3724/SP.J.1087.2013.01115

计算机应用 ›› 2013, Vol. 33 ›› Issue (04): 1115-1118.DOI: 10.3724/SP.J.1087.2013.01115

基于线性规划和相似变换的点匹配算法

赵宇兰¹,连玮²

1. 山西大学商务学院信息学院，太原 030031
2. 长治学院计算机系，山西长治 046011

收稿日期:2012-10-29 修回日期:2012-12-09 出版日期:2013-04-01 发布日期:2013-04-23
通讯作者: 赵宇兰
作者简介:赵宇兰(1979-),女,山西晋中人,讲师,硕士研究生,主要研究方向：计算机视觉与图像处理、数据库系统；连玮(1977-),男,山西长治人,讲师,博士研究生,主要研究方向：计算机视觉与图像处理、图形图像与模式识别。

Point matching based on linear programming with similarity regularization

ZHAO Yulan¹,LIAN Wei²

1. Information Faculty, Business College of Shanxi University,Taiyuan Shanxi 030031, China
2. Department of Computer Science, Changzhi College,Changzhi Shanxi 046011, China

Received:2012-10-29 Revised:2012-12-09 Online:2013-04-01 Published:2013-04-23
Contact: ZHAO Yulan

摘要/Abstract

摘要： 为解决点匹配过程中非刚性形变、位置噪声和出格点等因素导致点匹配不理想的问题，提出一种基于线性规划和相似变换的特征点匹配算法。点匹配被建模成一个能量函数最小化问题。在该函数中，形状上下文特征用于降低点对应关系的歧义性，相似变换用于保持空间映射的连续性，连续松弛问题归结为一个线性规划。仿真结果证实了该算法的有效性。

关键词: 线性规划, 点匹配, 对应关系, 形状上下文, 图像处理

Abstract: This paper proposed a linear programming based point matching method with similarity regularization in order to resolve the problems of non-rigid deformation, positional noise and outliers. Point matching was modeled as an energy minimization problem. Shape context was used to reduce the ambiguity of point correspondence, and similarity transform was used to preserve the continuity of spatial mapping. The continuously relaxed optimization problem is reduced to a linear program where optimality can be guaranteed. The simulation results verified the effectiveness of the method.

Key words: linear programming, point matching, point correspondence, shape context, image processing

中图分类号:

TP391.41

赵宇兰连玮. 基于线性规划和相似变换的点匹配算法[J]. 计算机应用, 2013, 33(04): 1115-1118.

ZHAO Yulan LIAN Wei. Point matching based on linear programming with similarity regularization[J]. Journal of Computer Applications, 2013, 33(04): 1115-1118.

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基于线性规划和相似变换的点匹配算法

Point matching based on linear programming with similarity regularization

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