Constructing arrangements of lines and hyperplanes with applications
SIAM Journal on Computing
A survey of image registration techniques
ACM Computing Surveys (CSUR)
Geometric matching under noise: combinatorial bounds and algorithms
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Digital image analysis: selected techniques and applications
Digital image analysis: selected techniques and applications
A Rotation Invariant Filter for Two-Dimensional String Matching
CPM '98 Proceedings of the 9th Annual Symposium on Combinatorial Pattern Matching
Algorithmic Applications of Low-Distortion Geometric Embeddings
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
Two-dimensional pattern matching with rotations
Theoretical Computer Science
Sequential and indexed two-dimensional combinatorial template matching allowing rotations
Theoretical Computer Science
Handbook of Image and Video Processing (Communications, Networking and Multimedia)
Handbook of Image and Video Processing (Communications, Networking and Multimedia)
Real Two Dimensional Scaled Matching
Algorithmica
On the asymptotic and practical complexity of solving bivariate systems over the reals
Journal of Symbolic Computation
Theoretical Computer Science
Two-dimensional pattern matching with rotations
CPM'03 Proceedings of the 14th annual conference on Combinatorial pattern matching
Faster two dimensional scaled matching
CPM'06 Proceedings of the 17th Annual conference on Combinatorial Pattern Matching
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Two-dimensional pattern matching with scaling and rotation for given pattern P and text T is the computational problem of finding a subtext in T such that a scaled and rotated transformation of P most accurately resembles the subtext. Applications of pattern matching are found, for instance, in computer vision, medical imaging, pattern recognition and watermarking. All known approaches to find a globally optimal matching depend on the basic nearest-neighbor interpolation. To use higher-order interpolations, current algorithms apply numerical techniques that provide only locally optimal solutions. This paper presents the first algorithm to find an optimal match under a large class of higher-order interpolation methods including bilinear and bicubic. The algorithm exploits a discrete characterization of the parameter space for scalings and rotations to achieve a polynomial time complexity.