TY - GEN
T1 - Extraction and specialization of geo-spatial objects in geo-images using semantic compression algorithm
AU - Guzmán, Giovanni
AU - Levachkine, Serguei
AU - Torres, Miguel
AU - Quintero, Rolando
AU - Moreno, Marco
PY - 2008
Y1 - 2008
N2 - This paper describes 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 is made in two levels (general and specialized). The aim of the labeling process is to associate a label of the thematic to each region, taking into account the RGB characteristics of the geo-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. As a result, the set of labels describes the semantics of a geo-image.
AB - This paper describes 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 is made in two levels (general and specialized). The aim of the labeling process is to associate a label of the thematic to each region, taking into account the RGB characteristics of the geo-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. As a result, the set of labels describes the semantics of a geo-image.
UR - http://www.scopus.com/inward/record.url?scp=57049096589&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-88636-555
DO - 10.1007/978-3-540-88636-555
M3 - Contribución a la conferencia
AN - SCOPUS:57049096589
SN - 3540886354
SN - 9783540886358
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 573
EP - 584
BT - MICAI 2008
T2 - 7th Mexican International Conference on Artificial Intelligence, MICAI 2008
Y2 - 27 October 2008 through 31 October 2008
ER -