Particle Tracking of Electrophoresis by Using Genetic Algorithm

This paper describes the new particle tracking method taking advantage of combinatorial optimization by the genetic algorithm. The particle tracking method has been investigated to search the identical particles between two sequential flow images. It is impossible to make a small number of particle combinations in the two images, but the identical particles are speedily found by using the genetic algorithm. Since the distance between combining particles is minimized in the identical particle when time difference between the two images is very small, we can apply the distances for exploring identical particles to the fitness function of genetic algorithm. The proper fitness function has the advantage that a large number of identical particles is discovered by one image process with the genetic algorithm. The particle tracking method has been induced by solution of optimization problem for the particle combinations. In addition, the method enables us to achieve the velocity measurement of particle movement caused by electrophoresis.