Reconstructing persistent graph structures from noisy images
Let a point cloud be a noisy dotted image of a graph on the plane. We present a new fast algorithm for reconstructing the original graph from the given point cloud. Degrees of vertices in the graph are found by methods of persistent topology. Necessary parameters are automatically optimized by machi...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/26521 |
| Acceso en línea: | http://hdl.handle.net/11441/26521 |
| Access Level: | acceso abierto |
| Palabra clave: | Graph reconstruction Noisy image Point cloud data Persistent topology |
| Sumario: | Let a point cloud be a noisy dotted image of a graph on the plane. We present a new fast algorithm for reconstructing the original graph from the given point cloud. Degrees of vertices in the graph are found by methods of persistent topology. Necessary parameters are automatically optimized by machine learning tools. |
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