DocumentCode
3336133
Title
Genetic Algorithm for distorted point set matching
Author
Jinwei Xu ; Jiankun Hu ; Xiuping Jia
Author_Institution
Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia
Volume
03
fYear
2013
fDate
16-18 Dec. 2013
Firstpage
1724
Lastpage
1729
Abstract
For image registration, point matching is still a fundamental problem because of the complex distortion such as transformation, missing and irrelevant points involved in two point sets detected from images. In this paper, a new method based on Genetic Algorithm (GA) is proposed to find the optimal affine transformation between two different point sets. In order to deal with the influence of the missing and spurious points, we define a fitness function in the combination of global topology of point set and individual point property. The experimental results on randomly generated 2D point sets demonstrate that the proposed GA-based point matching algorithm can achieve good performance in terms of correct matching (CM), false matching (FM), and missing matching (MM).
Keywords
genetic algorithms; image matching; image registration; CM; FM; GA-based point matching algorithm; MM; complex distortion; correct matching; distorted point set matching; false matching; fitness function; genetic algorithm; global topology; image registration; individual point property; missing matching; optimal affine transformation; point set; Biological cells; Feature extraction; Frequency modulation; Genetic algorithms; Image registration; Measurement; Robustness; genetic algorithm; image registration; point matching;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing (CISP), 2013 6th International Congress on
Conference_Location
Hangzhou
Print_ISBN
978-1-4799-2763-0
Type
conf
DOI
10.1109/CISP.2013.6743954
Filename
6743954
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