Zoubir Talai and Yamina M.B. Ali
Homography, metaheuristic, particle swarm optimization
This paper proposes particle swarm optimization to solve the homography problem. The inputs are the corresponding points coordinates of two pictures that are related with homography. Each particle of the swarm is a vector with eight variables that are the subject of this optimization. The elements of this vector are the components of the homography matrix. A comparison with existing technique singular value decomposition (SVD) is done. Both computer simulation and real data have been used to test the proposed technique, and good results have been obtained. The main gain of this technique is the accuracy of results and easiness of implementation.
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