Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Binary Image Registration Using Covariant Gaussian Densities
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Parametric estimation of affine deformations of planar shapes
Pattern Recognition
Affine alignment of compound objects: a direct approach
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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We consider the estimation of linear transformations aligning a known binary shape and its distorted observation. The classical way to solve this registration problem is to find correspondences between the two images and then compute the transformation parameters from these landmarks. Here we propose a unified framework where the exact transformation is obtained as the solution of either a polynomial or a linear system of equations without establishing correspondences. The advantages of the proposed solutions are that they are fast, easy to implement, have linear time complexity, work without landmark correspondences and are independent of the magnitude of transformation.