A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Regularization theory and neural networks architectures
Neural Computation
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms
International Journal of Computer Vision
Fusing Points and Lines for High Performance Tracking
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
On Image Registration in Magnetic Resonance Imaging
BMEI '08 Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02
Directly manipulated free-form deformation image registration
IEEE Transactions on Image Processing
Intensity based nonparametric image registration
Proceedings of the international conference on Multimedia information retrieval
Fair: Flexible Algorithms for Image Registration
Fair: Flexible Algorithms for Image Registration
Intensity-Based Image Registration by Nonparametric Local Smoothing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine learning for high-speed corner detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Efficient, robust, and fast global motion estimation for video coding
IEEE Transactions on Image Processing
Fingerprint registration by maximization of mutual information
IEEE Transactions on Image Processing
A contour-based approach to multisensor image registration
IEEE Transactions on Image Processing
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Image registration (IR) aims to geometrically match one image to another. It is extensively used in many imaging applications. Among many existing IR methods, one widely used group of methods are feature-based. By a feature-based method, a number of relevant image features are first extracted from the two images, respectively, and then a geometric matching transformation is found to best match the two sets of features. However, proper identification and extraction of image features turns out to be a challenging task. Generally speaking, a good image feature extraction method should have the following two properties: (i) the identified image features should provide us proper information to approximate the geometric matching transformation accurately, and (ii) they should be easy to identify by a computer algorithm so that the entire feature extraction procedure is computer automatic. In this paper, a new type of image features is studied, which has the two properties described above. Together with the widely used thin plate spline (TPS) geometric transformation model, it is shown that our feature-based IR method works effectively in various cases.