Retinal image registration using geometrical features.
In this study, we have introduced an accurate retinal images registration method using affine moment invariants (AMI's) which are the shape descriptors. First, some closed-boundary regions are extracted in both reference and sensed images. Then, AMI's are computed for each of those regions. The centers of gravity of three pairs of regions which have the minimum of distances are selected as the control points. The region matching is performed by the distance measurements of AMI's. The evaluation of region matching is performed by comparing the angles of three triangles which are built on these three-point pairs in reference and sensed images. The parameters of affine transform can be computed using these three pairs of control points. The proposed algorithm is applied on the valid DRIVE database. In general (for the case, each sensed image is produced by rotating, scaling, and translating the reference image with different angles, scale factors, and translation factors), the success rate and accuracy is 95 and 96 %, respectively.
Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran. s_gharabaghi@sut.ac.ir
Sara
S
Gharabaghi
Sabalan
S
Daneshvar
Mohammad Hossein
MH
Sedaaghi
D000465:Algorithms; D016208:Databases, Factual; D003952:Diagnostic Imaging / Q000379:methods*; D005451:Fluorescein Angiography / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D012160:Retina / Q000033:anatomy & histology* / Q000473:pathology*; D012161:Retinal Artery / Q000033:anatomy & histology / Q000473:pathology; D012169:Retinal Vein / Q000033:anatomy & histology / Q000473:pathology; D012680:Sensitivity and Specificity