Retinal Image Matching Using Hierarchical Vascular Features

Joint Authors

Ramamohanarao, Kotagiri
Nath, Baikunth
Bhuiyan, Alauddin
Wong, Tien Y.
Lamoureux, Ecosse

Source

Computational Intelligence and Neuroscience

Issue

Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-7, 7 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2011-10-13

Country of Publication

Egypt

No. of Pages

7

Main Subjects

Biology

Abstract EN

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.

American Psychological Association (APA)

Bhuiyan, Alauddin& Lamoureux, Ecosse& Nath, Baikunth& Ramamohanarao, Kotagiri& Wong, Tien Y.. 2011. Retinal Image Matching Using Hierarchical Vascular Features. Computational Intelligence and Neuroscience،Vol. 2011, no. 2011, pp.1-7.
https://search.emarefa.net/detail/BIM-495634

Modern Language Association (MLA)

Bhuiyan, Alauddin…[et al.]. Retinal Image Matching Using Hierarchical Vascular Features. Computational Intelligence and Neuroscience No. 2011 (2011), pp.1-7.
https://search.emarefa.net/detail/BIM-495634

American Medical Association (AMA)

Bhuiyan, Alauddin& Lamoureux, Ecosse& Nath, Baikunth& Ramamohanarao, Kotagiri& Wong, Tien Y.. Retinal Image Matching Using Hierarchical Vascular Features. Computational Intelligence and Neuroscience. 2011. Vol. 2011, no. 2011, pp.1-7.
https://search.emarefa.net/detail/BIM-495634

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-495634