Automatic quantitative evaluation of image registration techniques with the ε dissimilarity criterion in the case of retinal images
Author(s) -
Ola Suleiman Ahmad,
Johan Debayle,
Nesrine Gherras,
Benoît Presles,
JeanCharles Pinoli,
Gilles Févotte
Publication year - 2011
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.890883
Subject(s) - artificial intelligence , computer vision , computer science , image registration , process (computing) , field of view , image (mathematics) , pattern recognition (psychology) , operating system
International audienceIn 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
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