Retinal image matching using hierarchical vascular features.
We propose a method for retinal image matching that can be used in image matching for person identification or patient longitudinal study. Vascular invariant features are extracted from the retinal image, and a feature vector is constructed for each of the vessel segments in the retinal blood vessels. The feature vectors are represented in a tree structure with maintaining the vessel segments actual hierarchical positions. Using these feature vectors, corresponding images are matched. The method identifies the same vessel in the corresponding images for comparing the desired feature(s). Initial results are encouraging and demonstrate that the proposed method is suitable for image matching and patient longitudinal study.
Department of Computer Science and Software Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia. abhuiyan@unimelb.edu.au
Alauddin
A
Bhuiyan
Ecosse
E
Lamoureux
Baikunth
B
Nath
Kotagiri
K
Ramamohanarao
Tien Y
TY
Wong
D056667:Biometric Identification / Q000379:methods; D003952:Diagnostic Imaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008137:Longitudinal Studies / Q000379:methods; D059906:Neuroimaging / Q000379:methods*; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012160:Retina / Q000033:anatomy & histology* / Q000502:physiology; D012161:Retinal Artery / Q000033:anatomy & histology* / Q000502:physiology