Guest editorial: Image fusion: Advances in the state of the art
Information Fusion
Consistent parameter clustering: Definition and analysis
Pattern Recognition Letters
Image registration using robust M-estimators
Pattern Recognition Letters
Crease detection from fingerprint images and its applications in elderly people
Pattern Recognition
Efficient cumulative matching for image registration
Image and Vision Computing
Automatic image registration via clustering and convex hull vertices matching
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Two-dimensional object recognition by matching local properties of contour points
Pattern Recognition Letters
3D object pose form clustering with multiple views
Pattern Recognition Letters
Hi-index | 0.14 |
A new technique is presented for matching image features to maps or models. The technique forms all possible pairs of image features and model features which match on the basis of local evidence alone. For each possible pair of matching features the parameters of an RST (rotation, scaling, and translation) transformation are derived. Clustering in the space of all possible RST parameter sets reveals a good global transformation which matches many image features to many model features. Results with a variety of data sets are presented which demonstrate that the technique does not require sophisticated feature detection and is robust with respect to changes of image orientation and content. Examples in both cartography and object detection are given.