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A new image segmentation hybrid algorithm
- Source :
- 2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI).
- Publication Year :
- 2012
- Publisher :
- IEEE, 2012.
-
Abstract
- A new hybrid algorithm for image segmentation based on k-mean and particle swarm optimization algorithm is proposed in the paper. K-mean clustering algorithm is a local search algorithm because it is easily to be trapped in local optimum and is sensitive to initial value effectively. On the other hand, particle swarm optimization algorithm is a global optimization algorithm. Because of taking the criterion function of k-mean as the object function of PSO, this algorithm incorporates the local search ability of k-mean algorithm with the global optimization ability of PSO. Experiments show that the new algorithm can get the optimal quantizated image by PSNR and RMSE.
- Subjects :
- Linde–Buzo–Gray algorithm
Meta-optimization
Computer science
business.industry
Population-based incremental learning
Computer Science::Neural and Evolutionary Computation
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Pattern recognition
Hybrid algorithm
Search algorithm
Artificial intelligence
Multi-swarm optimization
Difference-map algorithm
business
FSA-Red Algorithm
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)
- Accession number :
- edsair.doi...........5f30669aeb7b514a21bd307f896b993f