Abstract
Three novel object's contour detection schemes based on image fusion are proposed in this paper. In these schemes an active contour model is applied to detect the object's contour edge. Since an object's contour in an infrared (IR) image is usually clearer than that in a visible image, the convergent active contour in a visible image is improved with that in an IR image. The first contour detection scheme is realized by revising the shape-preserving active contour model. The second scheme minimizes the B-spline L2 norm's square of the difference of the B-spline control point vectors in two modal images. Contour tracking and extraction experiments indicate that the first scheme outperforms the second one. Moreover, a third scheme based on the active contour and pixel-level image fusion is proposed for images with incomplete but complementary scene information. An example using contour extraction of a partially hidden tank proves its efficacy.
Original language | English |
---|---|
Pages (from-to) | 2857-2870 |
Number of pages | 14 |
Journal | International Journal of Computer Mathematics |
Volume | 87 |
Issue number | 13 |
DOIs | |
Publication status | Published - Oct 2010 |
Keywords
- active contour
- contour detection
- feature-level fusion
- image fusion
- image processing