SciELO - Scientific Electronic Library Online

 
vol.14 número4Modelo auto regresivo no lineal basado en redes neuronales multicapa para pronóstico de series temporales índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • No hay artículos similaresSimilares en SciELO

Compartir


Computación y Sistemas

versión On-line ISSN 2007-9737versión impresa ISSN 1405-5546

Resumen

GUZMAN LUGO, José Giovanni. General Algorithm for the Semantic Decomposition of Geo-Image. Comp. y Sist. [online]. 2011, vol.14, n.4, pp.437-450. ISSN 2007-9737.

The thesis presents an object oriented methodology for the semantic extraction of a geo-image which is defined by a set of natural language labels. The approach is composed of two main stages: analysis and synthesis. The analysis stage detects the main geographic components of a geo-image by means of the color quantification, geometry and topology of the geospatial objects. The result of this stage is a set of geo-images with intensities that are approximately uniform. The synthesis stage extracts the main geographic objects that have been identified and a labeling process in two levels (general and specialized), which is equivalent to consider both local and global information of a geo-image. The aim of the general labeling process is to associate a label of the adequate thematic to each region, taking into account the RGB characteristics of the image. In order to specialize each geographic object, we have proposed a specialization algorithm that considers geometric and topologic relations among them, represented in geographic application domain ontology. The obtained set of labels describes the geo-image semantics.

Palabras llave : Image Processing and Computer Vision; Scene Analysis; Object Recognition.

        · resumen en Español     · texto en Inglés     · Inglés ( pdf )

 

Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons