Authors:
M. Fernandes
;
Y. Gavet
and
J. C. Pinoli
Affiliation:
Centre Ingénierie et Santé, Ecole Nationale Supérieure des Mines; Laboratoire des Procédés en Milieux Granulaires (LPMG), UMR CNRS 5148, France
Keyword(s):
Feature-based registration, Retinal images, Opthalmology, Local transformation, Dense transformation.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Image Registration
;
Informatics in Control, Automation and Robotics
;
Matching Correspondence and Flow
;
Motion, Tracking and Stereo Vision
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
A method for spatial registering pairs of digital images of the retina is presented, using intrinsic feature points (landmarks) and dense local transformation. First, landmarks, i.e. blood vessel bifurcations, are extracted from both retinal images using filtering followed by thinning and branch point analysis. Correspondances are found by topological and structural comparisons between both retinal networks. From this set of matching points, a displacement field is computed and, finally, one of the two images is transformed. Due to complex retinal registration problem, the presented transformation is dense, local and adaptive. Expermimental results established the effectiveness and the interest of the dense registration method.