MATCHING - INVARIANT TO TRANSLATIONS, ROTATIONS AND SCALE CHANGES

被引：80

作者：

LI, SZ ^{[1
]}

机构：

[1] UNIV SURREY,DEPT ELECTR & ELECT ENGN,GUILDFORD GU2 5XH,SURREY,ENGLAND

来源：

PATTERN RECOGNITION | 1992年 / 25卷 / 06期

关键词：

ATTRIBUTED RELATIONAL STRUCTURES; INVARIANCE; PATTERN RECOGNITION; RELAXATION LABELING; SUB-GRAPH MATCHING;

D O I：

10.1016/0031-3203(92)90075-T

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An optimization approach to invariant matching is proposed. In this approach, an object or a pattern is invariantly represented by an object-centred description called an attributed relational structure (ARS) embedding invariant properties and relations between the primitives of the pattern such as line segments and points. Noise effect is taken into account such that a scene can consist of noisy sub-parts of a model. The matching is then to find the optimal mapping between the ARSs of the scene and the model. A gain functional is formulated to measure the goodness of fit and is to be maximized by using the relaxation labelling method. Experiments are shown to illustrate the matching algorithm and to demonstrate that the approach is truly invariant to arbitrary translations, rotations, and scale changes under noise.

引用

页码：583 / 594

页数：12

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