Automatic quantitative evaluation of image registration techniques with the "epsilon" dissimilarity criterion in the case of retinal images.

Yann Gavet (1, 2, 3, 4) , Mathieu Fernandes (1, 2, 3, 4) , Jean-Charles Pinoli (1, 2, 3, 4)

1 CIS-ENSMSE - Centre Ingénierie et Santé
2 DIM-ENSMSE - Département Imagerie et Morphologie
3 LPMG-EMSE - Laboratoire des Procédés en Milieux Granulaires
4 IFRESIS - Institut Fédératif de Recherche en Sciences et Ingénierie de la Santé

In human retina observation (with non mydriatic optical microscopes), a registration process is often employed to enlarge the field of view. For the ophthalmologist, this is a way to spare time browsing all the images. A lot of techniques have been proposed to perform this registration process, and indeed, its good evaluation is a question that can be raised. This article presents the use of the "epsilon" dissimilarity criterion to evaluate and compare some classical featurebased image registration techniques. The problem of retina images registration is employed as an example, but it could also be used in other applications. The images are first segmented and these segmentations are registered. The good quality of this registration is evaluated with the "epsilon" dissimilarity criterion for 25 pairs of images with a manual selection of control points. This study can be useful in order to choose the type of registration method and to evaluate the results of a new one.

Mots clés: Dissimilarity criterion; Image registration; Human retina

Domaines: Génie des procédés; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Yann Gavet, Mathieu Fernandes, Jean-Charles Pinoli. Automatic quantitative evaluation of image registration techniques with the "epsilon" dissimilarity criterion in the case of retinal images.. Tenth International Conference on Quality Control by Artificial Vision QVAC 2011, Jun 2011, Saint Etienne, France. pp.8000-23, ⟨10.1117/12.890883⟩. ⟨hal-00614076⟩