An evolutionary tabu search for cell image segmentation

Many problems in practically all fields of science, engineering and technology involve global optimization. It becomes more and more important to develop the efficient global optimization approach to these problems. In this paper, an evolutionary tabu search is developed and it is applied to cell image segmentation. The advantages of both genetic algorithm and tabu search algorithm are combined in our method. Specifically, we incorporates "the survival of strongest idea" of evolution algorithm into tabu search. The results on the segmentation of noisy human thyroid and small intestine cell images show that our method has the ability to find the global optimum, which not only keeps the advantages of tabu search and genetic algorithms, but also overcomes some of their shortages. By comparing our algorithm with the existing other global optimization methods (such as genetic algorithm, tabu search), we find that the new method is more practical and effective, which also yields g...

• Type: Journal
• Year: 2002
• Where: TSMC
• Authors: Tianzi Jiang, Faguo Yang
• Keywords: Genetic Algorithm, Global Optimization, Tabu Search, TSMC 2002