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
Link To Document :
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