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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Guo Yutang Liu Lulu |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Comput. Sci. & Technol, Hefei Normal Coll., Hefei (Guo Yutang; Liu Lulu) |
| Abstract | In order to improve the convergence rate of the genetic algorithm based on edge detection, a novel edge detection method based on good point set genetic algorithm(GGA) was proposed. The proposed method first redesigns the crossover operation by using the theory of good point set in which progeny inherits the common genes of parents which represent its family so as to improve the convergence rate of the genetic algorithm. Furthermore, the proposed method offers another better way to improve the convergence rate, that is, to reduce solution domain by pre-processing image to filtering non edge pixel before the algorithm executing. Experimental results show the proposed algorithm performs very well in terms of convergence rate. The detected edge image is well localized, and thin, and robust to noise. |
| Starting Page | 587 |
| Ending Page | 591 |
| File Size | 455709 |
| Page Count | 5 |
| File Format | |
| ISBN | 9787900719706 |
| DOI | 10.1109/CHICC.2008.4605754 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-07-16 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute Of Intelligence M&C Technical Of KMUST |
| Subject Keyword | Filtering Image edge detection Genetic algorithm Artificial neural networks Fuzzy entropy Entropy Electronic mail Edge detection Good set Genetic algorithms Convergence |
| Content Type | Text |
| Resource Type | Article |
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