Artículo
Topology-based image segmentation using LBP pyramids
Autor/es | Cerman, Martin
Janusch, Ines González Díaz, Rocío Kropatsch, Walter G. |
Departamento | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) |
Fecha de publicación | 2016 |
Fecha de depósito | 2021-10-18 |
Publicado en |
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Resumen | 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, ... 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. |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España |
Identificador del proyecto | MTM2015-67072-P |
Cita | Cerman, M., Janusch, I., González Díaz, R. y Kropatsch, W.G. (2016). Topology-based image segmentation using LBP pyramids. Machine Vision and Applications, 27 (8), 1161-1174. |
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