Belief decision support and reject for textured images characterization

Arnaud Martin (1)

1 E3I2 - Extraction et Exploitation de l'Information en Environnements Incertains

The textured images' classification assumes to consider the images in terms of area with the same texture. In uncertain environment, it could be better to take an imprecise decision or to reject the area corresponding to an unlearning class. Moreover, on the areas that are the classification units, we can have more than one texture. These considerations allows us to develop a belief decision model permitting to reject an area as unlearning and to decide on unions and intersections of learning classes. The proposed approach finds all its justification in an application of seabed characterization from sonar images, which contributes to an illustration.

Mots clés: textured images; Belief decision; reject; belief function theory; pattern recognition; textured images.

Domaines: Informatique; Traitement du signal et de l'image [eess.SP]; Intelligence artificielle [cs.AI]; Traitement du signal et de l'image [eess.SP]

Arnaud Martin. Belief decision support and reject for textured images characterization. International Conference on Information Fusion, Oct 2008, Lens, France. pp.131. ⟨hal-00293209⟩