Paper
20 September 2001 Whitening transformation and robust estimation technique applied to point pattern matching
Zhonggen Yang
Author Affiliations +
Proceedings Volume 4552, Image Matching and Analysis; (2001) https://doi.org/10.1117/12.441527
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China
Abstract
Matching and parameter estimation of two point patterns related through an affine transform is a very important research topic in the field of computer vision. The key step is to find some invariant features. As contrast to traditional techniques employing geometric moments or cross- ratios, the unique and orthonormal coordinate system, i.e. the eigen one, whose polar radiuses are invariant to an affine transform, is considered. Then, by using SVD, it is shown that after using a whitening transformation, the two point patterns related through an affine transform are respectively mapped to the eigen point patterns related through a rotation transformation. Based on this, an algorithm exactly estimating the affine parameters and correctly determining point correspondence on the condition that the only a priori knowledge is that the two patterns are corresponding in pattern-to-pattern way is developed. By fusing it with a robust estimation technique, which utilizes randomly sampling minimum redundant subset concept, K- RANSAC-wise architecture, joint criterion of maximum matching point pair support and minimum matching error, and linear optimal refinement procedure, we develop the robust version of the algorithm. The experiments have demonstrated that the proposed algorithm is very robust, exact and efficient.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhonggen Yang "Whitening transformation and robust estimation technique applied to point pattern matching", Proc. SPIE 4552, Image Matching and Analysis, (20 September 2001); https://doi.org/10.1117/12.441527
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KEYWORDS
Algorithm development

Evolutionary algorithms

Error analysis

Computer vision technology

Machine vision

Detection and tracking algorithms

Image analysis

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