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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lang Liu Yong Liu Ying Lin |
| Copyright Year | 2009 |
| Abstract | A new algorithm for adaptive threshold segmentation based on combining Fisher criterion with location optimization is proposed in this paper. Fisher criterion is taking as the fitness function of Genetic Algorithm (GA), and an adaptive method which is used to calculate crossover probability and mutation probability is presented. Meanwhile, we add a new local optimization operator that solves the disadvantages of poor astringency and premature occurrence in GA. Experimental results show that the algorithm achieves better performance on convergence and robustness¿can efficiently segment the details and converge the optimal threshold. |
| Starting Page | 78 |
| Ending Page | 80 |
| File Size | 372224 |
| Page Count | 3 |
| File Format | |
| ISBN | 9780769536439 |
| DOI | 10.1109/ISECS.2009.50 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-05-22 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image recognition Adaptive algorithm Image edge detection Optimization methods Probability threshold segmentation Electronic commerce Security adaptive Genetic Algorithm local optimization operator Genetic algorithms Image segmentation Fisher criterion Pixel |
| Content Type | Text |
| Resource Type | Article |
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