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Retina Identification Based on Moment Invariant

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Conference

2015 ASEE Annual Conference & Exposition

Location

Seattle, Washington

Publication Date

June 14, 2015

Start Date

June 14, 2015

End Date

June 17, 2015

ISBN

978-0-692-50180-1

ISSN

2153-5965

Conference Session

Curricular Issues in Computing and Information Technology Programs I

Tagged Division

Computing & Information Technology

Tagged Topic

Diversity

Page Count

16

Page Numbers

26.10.1 - 26.10.16

DOI

10.18260/p.23343

Permanent URL

https://peer.asee.org/23343

Download Count

56

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Paper Authors

biography

Alireza Kavianpour DeVry University, Pomona

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Dr. Alireza Kavianpour received his PH.D. Degree from University of Southern California (USC). He is currently Senior Professor at DeVry University, Pomona, CA. Dr. Kavianpour is the author and co-author of over forty technical papers all published in IEEE Journals or referred conferences. Before joining DeVry University he was a researcher at the University of California, Irvine and consultant at Qualcom Inc. His main interests are in the areas of embedded systems and computer architecture.

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Simin Shoari

biography

Behdad Kavianpour University of California, Irvine

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Researcher at the Gavin Herbert Eye Institute in the University of California, Irvine.

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Abstract

Retina Identification Based on Moment InvariantAbstractIn this paper, we present an algorithm for accurate recognition of an individual’s identity basedon a digitally represented image of the scanned retina. The technology is based upon the fact thatno two retinal patterns are alike.The identification algorithm for three-dimensional retinal imaging is based on using the momentinvariant concept. The mathematical foundation of an invariant feature is related to the theorythat images taken from different angles from the same object have the same set of momentinvariants. Moments contain information of an image which can be used in calculating the locationand orientation of the retinal image.Three-dimensional moment is used as a feature in detecting retinal images, which are modeled asellipsoids. Based on the moment principle, the proposed method can be employed to determinethe nine parameters of an ellipsoidal shape in a retinal image. These nine parameters include thecoordinates of the center of the ellipsoid, the length of major, minor, intermediate axes, and thedirection of three axes. A simulation program for retinal detection is employed.Key Word: Ellipsoid, image processing, pattern recognition, parallel algorithm, Retina, three-dimensional moments.

Kavianpour, A., & Shoari, S., & Kavianpour, B. (2015, June), Retina Identification Based on Moment Invariant Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23343

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