A concurrent region growing algorithm guided by circumscribed contours
Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2000 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10256/2175 |
| Acceso en línea: | http://hdl.handle.net/10256/2175 |
| Access Level: | acceso abierto |
| Palabra clave: | Algorismes computacionals Imatges -- Processament Reconeixement de formes (Informàtica) Visió per ordinador Computer algorithms Computer vision Image processing Pattern recognition systems |
| Sumario: | Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach |
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