Geometric Entities Voting Schemes in the Conformal Geometric Algebra Framework
| Autor: | Gehová López-González, Eduardo Bayro-Corrochano, Gerardo Altamirano-Gómez |
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| Rok vydání: | 2015 |
| Předmět: |
Applied Mathematics
media_common.quotation_subject 020208 electrical & electronic engineering Universal geometric algebra Geometric transformation ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Conformal geometric algebra 02 engineering and technology Function (mathematics) Real image Hough transform law.invention Algebra Randomized Hough transform law Computer Science::Computer Vision and Pattern Recognition Voting 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing ComputingMethodologies_COMPUTERGRAPHICS Mathematics media_common |
| Zdroj: | Advances in Applied Clifford Algebras. 26:1045-1059 |
| ISSN: | 1661-4909 0188-7009 |
| DOI: | 10.1007/s00006-015-0589-y |
| Popis: | Traditional methods for geometric entities resort to the Hough transform and tensor voting schemes for detect lines and circles. In this work, the authors extend these approaches using representations in terms of k-vectors of the Conformal Geometric Algebra. Of interest is the detection of lines and circles in images, and planes, circles, and spheres in the 3-D visual space; for that, we use the randomized Hough transform, and by means of k-blades we code such geometric entities. Motivated by tensor voting, we have generalized this approach for any kind of geometric entities or geometric flags formulating the perceptual saliency function involving k-vectors. The experiments using real images show the performance of the algorithms. |
| Databáze: | OpenAIRE |
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