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Identification of circles from datapoints using Gaussian sums
We present a pattern recognition method which use datapoints on a plane and estimates the parameters of a circle. MC data are generated in order to test the method's efficiency over noise hits, uncertainty in the hits positions and number of datapoints. The scenario were the hits from a quadran...
| Autores principales: | , , , , |
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| Lenguaje: | eng |
| Publicado: |
2014
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1016/j.nima.2014.01.046 http://cds.cern.ch/record/1669700 |
| _version_ | 1780935547118682112 |
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| author | Alexopoulos, T Iakovidis, G Leontsinis, S Ntekas, K Polychronakos, V |
| author_facet | Alexopoulos, T Iakovidis, G Leontsinis, S Ntekas, K Polychronakos, V |
| author_sort | Alexopoulos, T |
| collection | CERN |
| description | We present a pattern recognition method which use datapoints on a plane and estimates the parameters of a circle. MC data are generated in order to test the method's efficiency over noise hits, uncertainty in the hits positions and number of datapoints. The scenario were the hits from a quadrant of the circle are missing is also considered. The method proposed is proven to be robust, accurate and very efficient. |
| id | cern-1669700 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2014 |
| record_format | invenio |
| spelling | cern-16697002021-05-03T20:36:05Zdoi:10.1016/j.nima.2014.01.046http://cds.cern.ch/record/1669700engAlexopoulos, TIakovidis, GLeontsinis, SNtekas, KPolychronakos, VIdentification of circles from datapoints using Gaussian sumsDetectors and Experimental TechniquesMathematical Physics and Mathematics2: Common software tools2.3: Reconstruction toolkit for HEPWe present a pattern recognition method which use datapoints on a plane and estimates the parameters of a circle. MC data are generated in order to test the method's efficiency over noise hits, uncertainty in the hits positions and number of datapoints. The scenario were the hits from a quadrant of the circle are missing is also considered. The method proposed is proven to be robust, accurate and very efficient.In this paper we present a method of reconstructing the circle parameters from a set of datapoints on a plane. The method is based on the geometrical Legendre transform. We test the method under various scenarios using Monte Carlo generated data. These scenarios include variation of the noise hits percentage, uncertainties in the hit position and the number of datapoints. The technique is proven to be robust and provide quickly and effciently very accurate results. Furthermore, the use of the geometrical Legendre transform method for the identifcation of two overlapping circles is shown.arXiv:1403.4413AIDA-PUB-2014-002oai:cds.cern.ch:16697002014-03-18 |
| spellingShingle | Detectors and Experimental Techniques Mathematical Physics and Mathematics 2: Common software tools 2.3: Reconstruction toolkit for HEP Alexopoulos, T Iakovidis, G Leontsinis, S Ntekas, K Polychronakos, V Identification of circles from datapoints using Gaussian sums |
| title | Identification of circles from datapoints using Gaussian sums |
| title_full | Identification of circles from datapoints using Gaussian sums |
| title_fullStr | Identification of circles from datapoints using Gaussian sums |
| title_full_unstemmed | Identification of circles from datapoints using Gaussian sums |
| title_short | Identification of circles from datapoints using Gaussian sums |
| title_sort | identification of circles from datapoints using gaussian sums |
| topic | Detectors and Experimental Techniques Mathematical Physics and Mathematics 2: Common software tools 2.3: Reconstruction toolkit for HEP |
| url | https://dx.doi.org/10.1016/j.nima.2014.01.046 http://cds.cern.ch/record/1669700 |
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