GA approach to invariant matching: under noise and geometric transformations

Author

Weimin Huang ; Zhaoqi Bian

Author_Institution

Dept. of Autom., Tsinghua Univ., Beijing, China

Volume

2

fYear

1993

fDate

19-21 Oct. 1993

Firstpage

1021

Abstract

The paper proposes a new approach to solve the matching problem, in which the genetic algorithm is used as the search strategy to find the optimal matching between the features of the object and those of the model. Feature points matching is used as an example to discuss this kind of approach. Firstly the invariant relative attributes of features are discussed. With the invariant attributes, we analyse the expression of matching points. Secondly by using the genetic algorithm´s schema we design the new approach to the invariant matching. The experiments show that the algorithm is indeed invariant to the geometric transformations and it can work in the noise case.<>

Keywords

computational geometry; genetic algorithms; optimisation; pattern recognition; GA approach; feature points matching; genetic algorithm; geometric transformations; invariant matching; invariant relative attributes; matching problem; optimal matching; search strategy; Algorithm design and analysis; Automation; Distortion measurement; Equations; Genetic algorithms; Optimal matching; Shape; Solid modeling; Spatial databases;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '93. Proceedings. Computer, Communication, Control and Power Engineering.1993 IEEE Region 10 Conference on

Conference_Location

Beijing, China

Print_ISBN

0-7803-1233-3

Type

conf

DOI

10.1109/TENCON.1993.320187

Filename

320187