Learning imprecise semantic concepts from image databases.

Título inglés	Learning imprecise semantic concepts from image databases.
Título español	Aprendizaje de conceptos semánticos imprecisos a partir de bases de datos de imágenes.
Autor/es	Sánchez, Daniel ; Chamorro-Martínez, Jesús
Organización	Dep. Cienc. Comput. Intel. Artif. Univ. Granada, Granada, España
Revista	1134-5632
Publicación	2002, 9 (1): 59-73, 25 Ref.
Tipo de documento	articulo
Idioma	Inglés
Resumen inglés	In this paper we introduce a model to represent high-level semantic concepts that can be perceived in images. The concepts are learned and represented by means of a set of association rules that relate the presence of perceptual features to the fulfillment of a concept for a set of images. Since both the set of images where a perceptual feature appears and the set of images fulfilling a given concept are fuzzy, we use in fact fuzzy association rules for the learning model. The concepts so acquired are useful in several applications, in particular they provide a new way to formulate imprecise queries in image databases.
Clasificación UNESCO	110208
Palabras clave español	Lógica difusa ; Análisis digital de imágenes ; Recuperación de información
Código MathReviews	MR1956875
Código Z-Math	Zbl 1022.68045
Acceso al artículo completo