Abstract
A novel heuristic search algorithm based on sub-edge self-reinforce for edge extraction in noise image is proposed in this paper. Firstly, the noise image is filtered by a small scale Gaussian filter. Then a new Large Template Edge Detector is designed in order to get more accurate leading information, and the corresponding search trajectories are self-reinforced according to this information. Finally, the real edge of noise image is extracted according to the accumulated degree of self-reinforces. The new Large Template Edge Detector has good performance in orientation precision, noise resistance and false edge. Experimental results on image with noise demonstrate better performance of the proposed method, which keeps more image details in extracting real edges of objects, compared with the classical methods, especially Canny Operator.
| Original language | English |
|---|---|
| Pages (from-to) | 14-19 |
| Number of pages | 6 |
| Journal | Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence |
| Volume | 19 |
| Issue number | 1 |
| State | Published - Feb 2006 |
Keywords
- Canny operator
- Edge detection operator
- Edge extraction
- Heuristic search
- Small-scale Gaussian filtering
- Sub-edge reinforcement