A Genetic algorithm for the detection of 2D geometric primitives in images - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Rapport (Rapport De Recherche) Année : 1993

A Genetic algorithm for the detection of 2D geometric primitives in images

P. Martinez

Résumé

We investigate the use of genetic algorithms (GAs) in the framework of image primitives extraction (such as segments, circles, ellipses or quadrilaterals). This approach completes the well-known Hough transform, in the sense that GAs are efficient when the Hough approach becomes too expensive in memory, i.e. when we search for complex primitives having more than 3 or 4 parameters. Indeeda GA is a stochastic technique, relatively slow, but which provides with an efficient tool to search in a high dimensional space. The philosophy of the method is very similar to the Hough transform, which is to search an optimum in a parameter space. However, we will see that the implementation is different. The idea of using a GA for that purpose is not new, Roth and Levine have proposed a method for 2D and 3D primitives in 1992. For the detection of 2D primitives, we re-implement that method and improve it mainly in three ways : by using distance images instead of directly using contour images, which tends to smoothen the function to optimize, by using a GA-sharing technique, to detect several image primitives in the same step, by applying some recent theoretical results on GAs (about mutation probabilities) to reduce convergence time.

Domaines

Autre [cs.OH]
Fichier principal
Vignette du fichier
RR-2110.pdf (1.07 Mo) Télécharger le fichier

Dates et versions

inria-00074562 , version 1 (24-05-2006)

Identifiants

  • HAL Id : inria-00074562 , version 1

Citer

Evelyne Lutton, P. Martinez. A Genetic algorithm for the detection of 2D geometric primitives in images. [Research Report] RR-2110, INRIA. 1993. ⟨inria-00074562⟩
172 Consultations
213 Téléchargements

Partager

Gmail Facebook X LinkedIn More