Topology-based image segmentation using LBP pyramids
In this paper, we present a new image segmentation algorithmwhich is based on local binary patterns (LBPs) and the combinatorial pyramid and which preserves structural correctness and image topology. For this purpose, we define a codification of LBPs using graph pyramids. Since the LBP code characte...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/126666 |
| Acceso en línea: | https://hdl.handle.net/11441/126666 https://doi.org/10.1007/s00138-016-0795-1 |
| Access Level: | acceso abierto |
| Palabra clave: | Local binary patterns Irregular graph pyramid Primal and dual graph Topological characterization Image segmentation |
| Sumario: | In this paper, we present a new image segmentation algorithmwhich is based on local binary patterns (LBPs) and the combinatorial pyramid and which preserves structural correctness and image topology. For this purpose, we define a codification of LBPs using graph pyramids. Since the LBP code characterizes the topological category (local max, min, slope, saddle) of the gray level landscape around the center region, we use it to obtain a “minimal” image representation in terms of the topological characterization of a given 2D grayscale image. Based on this idea, we further describe our hierarchical texture aware image segmentation algorithm and compare its segmentation output and the “minimal” image representation. |
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