1. Application of an Improved Genetic Algorithm in Image Segmentation
- Author
-
Ao Min-si, Cheng Shi, Wu Yi-qi, and Lei Hui
- Subjects
Computer science ,business.industry ,Histogram ,Genetic algorithm ,Crossover ,Stability (learning theory) ,Algorithm design ,Pattern recognition ,Image segmentation ,Artificial intelligence ,business ,Evaluation function ,Selection (genetic algorithm) - Abstract
The selection of threshold is critical in image segmentation. Based on genetic algorithm, an improved method for selecting the optimal threshold in image segmentation is proposed. In the computational process, the improved GA adjusts crossover probability and mutation probability automatically according to the variance between the target and background, thus overcoming the problems of poor astringency and premature occurrence in Simple Genetic Algorithm. Moreover, the improved GA is used to find the optimum relation of the evaluation function on the basis of OTSU Principle in the paper. The experimental data demonstrate that this improved GA has a better convergence and stability than the Simple GA.
- Published
- 2008