Genetic algorithm based bubble matching and tracking in aerated water flows

In order to measure bubble characteristic parameters in the aerated water flows, a genetic algorithm (GA) and motion estimation based bubbles matching and tracking method is proposed. Because of considerable bubbles in each frame of the image sequences, the complex motion and the similarity of bubbles in size, shape and color in the flow field, the features based methods fell into inefficiency and could not solve the matching problem of bubbles. The presented method is very competent for solving the above problems and also efficient in accurately tracking the bubbles when whole kinetic occlusion happened.

[1]  Zbigniew Michalewicz,et al.  Evolutionary Algorithms, Homomorphous Mappings, and Constrained Parameter Optimization , 1999, Evolutionary Computation.

[2]  A Two-Phase Cinematic PIV Method for Bubbly Flows , 1997 .

[3]  Zbigniew Michalewicz,et al.  A Survey of Constraint Handling Techniques in Evolutionary Computation Methods , 1995 .

[4]  Lawrence Davis,et al.  Using a genetic algorithm to optimize problems with feasibility constraints , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[5]  Avraham A. Melkman,et al.  On-Line Construction of the Convex Hull of a Simple Polyline , 1987, Inf. Process. Lett..

[6]  Kenong Wu,et al.  Live cell image segmentation , 1995, IEEE Transactions on Biomedical Engineering.

[7]  Abdollah Homaifar,et al.  Constrained Optimization Via Genetic Algorithms , 1994, Simul..