Robust method of recovering epipolar geometry using messy genetic algorithm

2004 ◽  
Author(s):  
Mingxing Hu ◽  
Baozong Yuan ◽  
G. Dodds ◽  
Xiaofang Tang
Keyword(s):  
Genetic Algorithm ◽  
Epipolar Geometry ◽  
Robust Method

The genetic algorithm: A robust method for stress inversion

2017 ◽  
Vol 94 ◽  
pp. 227-239 ◽  
Author(s):  
Prithvi Thakur ◽  
Deepak C. Srivastava ◽  
Pravin K. Gupta
Keyword(s):  
Genetic Algorithm ◽  
Robust Method ◽  
Stress Inversion

scholarly journals Robust Method for Calculating the tRNA Adaptation Index utilizing the Genetic Algorithm

2021 ◽  
Author(s):  
Ali Mostafa Anwar ◽  
Saif M. Khodary ◽  
Mohamed Soudy ◽  
Eman Ali Ahmed ◽  
Aya Osama ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Robust Method ◽  
Adaptation Index

A GA-BASED APPROACH FOR EPIPOLAR GEOMETRY ESTIMATION

2013 ◽  
Vol 27 (08) ◽  
pp. 1355014 ◽  
Author(s):  
NEHAL KHALED ◽  
ELSAYED E. HEMAYED ◽  
MAGDA B. FAYEK
Keyword(s):  
Genetic Algorithm ◽  
Fundamental Matrix ◽  
Real Data ◽  
Epipolar Geometry ◽  
Optimum Estimation ◽  
Geometry Estimation

In this paper, a genetic algorithm (GA)-based approach to estimate the fundamental matrix is presented. The aim of the proposed GA-based algorithm is to reduce the effect of noise and outliers in the corresponding points which affect the accuracy of the estimated fundamental matrix. Although in the proposed approach the GA is allowed to select the significant among all detected points, on the average half of the matched points have been determined to give optimum estimation of the fundamental matrix. Experiments with synthetic and real data show that the proposed approach is accurate especially in the presence of a high percentage of outliers. The proposed GA can always obtain good results in both high and low detailed images. Even for low detailed images which have a small number of matched points available to estimate the fundamental matrix, the proposed GA outperformed other methods.

A robust method for partial deformed fingerprints verification using genetic algorithm

2009 ◽  
Vol 36 (2) ◽  
pp. 2008-2016 ◽  
Author(s):  
M.R. Girgis ◽  
A.A. Sewisy ◽  
R.F. Mansour
Keyword(s):  
Genetic Algorithm ◽  
Robust Method
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