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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Rahnamayan, S. Tizhoosh, H.R. |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Mechatron. Syst. Eng., Simon Fraser Univ., Vancouver, BC (Rahnamayan, S.) |
| Abstract | Image thresholding is a challenging task in image processing field. Many efforts have already been made to propose universal, robust methods to handle a wide range of images. Previously by the same authors, an optimization-based thresholding approach was introduced. According to the proposed approach, differential evolution (DE) algorithm, minimizes dissimilarity between the input grey-level image and the bi-level (thresholded) image. In the current paper, micro opposition-based differential evolution (micro-ODE), DE with very small population size and opposition-based population initialization, has been proposed. Then, it is compared with a well-known thresholding method, Kittler algorithm and also with its non-opposition-based version (micro-DE). In overall, the proposed approach outperforms Kittler method over 16 challenging test images. Furthermore, the results confirm that the micro-ODE is faster than micro-DE because of embedding the opposition-based population initialization. |
| Starting Page | 1409 |
| Ending Page | 1416 |
| File Size | 1878709 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424418220 |
| DOI | 10.1109/CEC.2008.4630979 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-06-01 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pixel Evolution (biology) Image processing Evolutionary computation Gold Convergence Robustness |
| Content Type | Text |
| Resource Type | Article |
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