Name
Abstract | ||
|---|---|---|
The contour alignment problem, considered in this letter, is to compute the minimal distance in a least-squares sense, between two explicitly represented contours, specified by corresponding points, after arbitrary rotation, scaling, and translation of one of the contours. This is a constrained nonlinear optimization problem with respect to the translation, rotation, and scaling parameters; however, it is transformed into an equivalent linear least-squares problem by a nonlinear change of variables. Therefore, a global solution of the contour alignment problem can be computed efficiently. It is shown that a normalized minimum value of the cost function is invariant to ordering and affine transformation of the contours and can be used as a measure for the distance between the contours. A solution is proposed to the problem of finding a point correspondence between the contours. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/LSP.2008.2008588 | IEEE SIGNAL PROCESSING LETTERS |
Keywords | Field | DocType |
Contour alignment, image registration, invariance, least squares, rotation, scaling, translation | Change of variables,Affine transformation,Least squares,Mathematical optimization,Nonlinear system,Invariant (physics),Nonlinear programming,Invariant (mathematics),Scaling,Mathematics | Journal |
Volume | Issue | ISSN |
16 | 1-3 | 1070-9908 |
Citations | PageRank | References |
4 | 0.45 | 13 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ivan Markovsky | 1 | 427 | 43.02 |
| Sasan Mahmoodi | 2 | 94 | 17.37 |