Enhancement of a genetic algorithm for affine invariant planar object shape matching using the migrant principle

The use of the migrant principle has proved to be effective in reducing the impact of the initial populations of genetic algorithms in optimising simple linear functions. Analytical and empirical results have also suggested that the method could be applied to locate an optimal solution in larger search space with more complex landscape. In the paper, an attempt has been made to develop an enhanced object matching technique that is based on the integration of the migrant principle and an existing genetic algorithm for affine invariant object recognition. As the latter had been taken as the foundation of a series of research works, any improvement on the scheme will directly benefit subsequent developments. The problem being addressed is highly nonlinear, which requires well-formed initial populations to attain successful matching of object shapes. Experimental results reveal that, for the same population size and mutation rate, the proposed method demonstrates significant improvement, as compared with its precedent, and that it is insensitive to the initial population.