Name
Abstract | ||
|---|---|---|
We propose a novel B-spline active contour model based on image fusion. Compared with conventional active contours, this active contour has two advantages. First, it is represented by a cubic B-spline curve, which can adaptively determine the curve parameter's step length; and it can also effectively detect and express the object contour's corner points. Second, it is implemented in connection with image fusion. Its external image force is modified as the weighted sum of two modal image forces, with the two weights in terms of a local region's image entropy or image contrast's standard deviation. The experiments indicate that this active contour can accurately detect both the object's contour edge and the corner points. Our experiments also indicate that the active contours convergence with a weighted image force by the image contrast's standard deviation is more accurate than that of image entropy, restraining the influence of the texture or pattern. (c) 2008 SPIE and IS&T. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1117/1.2898535 | JOURNAL OF ELECTRONIC IMAGING |
Keywords | Field | DocType |
image fusion,active contour model | Convergence (routing),Active contour model,External image,Computer vision,Pattern recognition,Image fusion,Feature detection (computer vision),Computer science,Object contour,Artificial intelligence,Standard deviation,Modal | Journal |
Volume | Issue | ISSN |
17 | 1 | 1017-9909 |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peng Zhao | 1 | 0 | 0.34 |
| Zhongliang Jing | 2 | 351 | 39.38 |
| Shiqiang Hu | 3 | 56 | 6.96 |