| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10360226 | Image and Vision Computing | 2005 | 9 Pages |
Abstract
A generic framework for automatically identifying features in images based on evolutionary computation is proposed here. The significant characteristic of the method is that it does not require segmentation. We use evolution strategies as the optimization algorithm to identify features. The system is based on a conjecture that certain filters will give prominent responses to certain features. The identified features are represented as regions enclosed within the chosen search structure-the ellipse. By defining filter response criteria as the fitness function, evolution strategies succeeds in finding the feature in a much more efficient way than, say, segmentation.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Xiaojing Yuan, Jian Zhang, Xiaohui Yuan, Bill P. Buckles,
