Presentación | Participantes | Bibliografía (DML-E) | Bibliografía adicional | Enlaces de interés | Otros proyectos DML | Ayuda  
INICIO | 27 de julio de 2024
  

Fuzzy sets in computer vision: an overview.

Título inglés Fuzzy sets in computer vision: an overview.
Título español Conjuntos difusos en visión artificial: una perspectiva general.
Autor/es Sobrevilla, Pilar ; Montseny, Eduard
Organización Dep. Mat. Apl. II Univ. Politèc. Catalunya, Barcelona, España;Dep. Engin. Sist. Automàt. Informàt. Ind. Univ. Politèc. Catalunya, Barcelona, España
Revista 1134-5632
Publicación 2003, 10 (2-3): 71-83, 76 Ref.
Tipo de documento articulo
Idioma Inglés
Resumen inglés Every computer vision level crawl with uncertainty, what makes its management a significant problem to be considered and solved when trying for automated systems for scene analysis and interpretation. This is why fuzzy set theory and fuzzy logic is making many inroads into the handling of uncertainty in various aspects of image processing and computer vision.
The growth within the use of fuzzy set theory in computer vision is keeping pace with the use of more complex algorithms addressed to solve problems arisen from image vagueness management.
Due to the natural linguistic capabilities of high-level computer vision, it is a very appropriate place for applying fuzzy sets. Moreover, scene description, i.e., the language-based representation of regions and their relationships, for either humans or higher automated reasoning provides an excellent opportunity. With this overview we want to address the various aspects of image processing and analysis problems where the theory of fuzzy sets has so far been applied. On the other hand, we will discuss the possibility of making fusion of the merits of fuzzy set theory, neural networks theory and genetic algorithms for improved performance. Finally a list of representative references is also provided.
Clasificación UNESCO 110208
Palabras clave español Lógica difusa ; Conjuntos difusos ; Visión artificial
Código Z-Math Zbl 1086.68622
Icono pdf Acceso al artículo completo
Equipo DML-E
Instituto de Ciencias Matemáticas (ICMAT - CSIC)
rmm()icmat.es