A new retinal recognition system using a logarithmic spiral sampling grid

Fabiola M. Villalobos Castaldi, Edgardo M. Felipe-Riveron, Ernesto Suaste Gómez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The retinal vascular network has many desirable characteristics as a basis for authentication, including uniqueness, stability, and permanence. In this paper, a new approach for retinal images features extraction and template coding is proposed. The use of the logarithmic spiral sampling grid in scanning and tracking the vascular network is the key to make this new approach simple, flexible and reliable. Experiments show that this approach can achieve the reduction of data dimensionality and of the required time to obtain the biometric code of the vascular network in a retinal image. The performed experiments demonstrated that the proposed verification system has an average accuracy of 95.0 - 98 %. © 2014 Springer International Publishing.
Original languageAmerican English
Title of host publicationA new retinal recognition system using a logarithmic spiral sampling grid
Pages241-250
Number of pages215
ISBN (Electronic)9783319074900
DOIs
StatePublished - 1 Jan 2014
EventLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -
Duration: 1 Jan 2014 → …

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8495 LNCS
ISSN (Print)0302-9743

Conference

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Period1/01/14 → …

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Villalobos Castaldi, F. M., Felipe-Riveron, E. M., & Gómez, E. S. (2014). A new retinal recognition system using a logarithmic spiral sampling grid. In A new retinal recognition system using a logarithmic spiral sampling grid (pp. 241-250). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8495 LNCS). https://doi.org/10.1007/978-3-319-07491-7_25