Authors:
Alauddin Bhuiyan
;
Baikunth Nath
;
Kotagiri Ramamohanarao
and
Tien Y. Wong
Affiliation:
The University of Melbourne Australia, Australia
Keyword(s):
Retinal image, Vessel bifurcation, Branch and crossover points, Invariant feature, Feature vector, Binary tree, Tree matching algorithm.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Biometrics
;
Biometrics and Pattern Recognition
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Multimedia
;
Multimedia Signal Processing
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
;
Telecommunications
Abstract:
In this paper, 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. An image matching method is demonstrated which identifies the same vessel in the corresponding images for comparing the desired feature(s). Initial results demonstrate that the method is suitable for image matching and patient longitudinal study.