Extracting meaningful curves from images

Frédéric Cao (1) , Pablo Musé (2) , Frédéric Sur (2)

1 VISTA - Vision spatio-temporelle et active
2 ENS Cachan - École normale supérieure - Cachan

Since the beginning, Mathematical Morphology has proposed to extract shapes from images as connected components of level sets. These methods have proved very efficient in shape recognition and shape analysis. In this paper, we present an improved method to select the most meaningful level lines (boundaries of level sets) from an image. This extraction can be based on statistical arguments, leading to a parameter free algorithm. It permits to roughly extract all pieces of level lines of an image, that coincide with pieces of edges. By this method, the number of encoded level lines is reduced by a factor 100, without any loss of shape contents. In contrast to edge detections algorithm or snakes methods, such a level lines selection method delivers accurate shape elements, without user parameter: no smoothing involved and selection parameters can be computed by Helmholtz Principle.

Mots clés: EDGE DETECTION; MATHEMATICAL MORPHOLOGY; TOPOGRAPHIC MAP; LEVEL LINES; HELMHOLTZ PRINCIPLE; GESTALT THEORY

Domaines: Autre [cs.OH]

Frédéric Cao, Pablo Musé, Frédéric Sur. Extracting meaningful curves from images. [Research Report] RR-5067, INRIA. 2003. ⟨inria-00071517⟩