A new spontaneous pupillary oscillation-based verification system

Villalobos-Castaldi, Fabiola M.; Suaste-Gómez, Ernesto

doi:10.1016/j.eswa.2013.03.042

Cited by 23 publications

(13 citation statements)

References 19 publications

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“…-Pupil segmentation: In the same way like its predecessor, standard procedure is performed, a threshold segmentation [4]. Because of the homogeneity of laboratory condition, the threshold level was adjusted to a normalized value of 0.035.…”

Section: B Digital Image Processingmentioning

confidence: 99%

“…Typically, this last task consists in some kind of filtering [10,12]. In this case, morphological operations was done (opening and close) [4].…”

Section: B Digital Image Processingmentioning

confidence: 99%

“…Some examples of clinical applications are studies of Type I-II Diabetes [6], Nervous system diseases [7] etc. whereas engineering application include but are not limited to Biometric systems [4] and Eye-trackers [8].…”

Section: Introductionmentioning

confidence: 99%

“…Some of the pupillary event of interest are the pupil cycle time [2], pupillary latency [3], hippus [4], also in an indirect form, ocular movements [5]. Some examples of clinical applications are studies of Type I-II Diabetes [6], Nervous system diseases [7] etc.…”

Section: Introductionmentioning

confidence: 99%

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Approximations of Pupillary Shape in High-Definition Video-Oculography Registers

Mora-Martínez

Suaste-Gómez

2017

VII Latin American Congress on Biomedical Engineering CLAIB 2016, Bucaramanga, Santander, Colombia, October 26th -28th, 2016

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Abstract-Two approximations of the pupillary shape (in laboratory environment) were developed: a nonlinear elliptic fit with outliers rejection and the assessment of the realistic amorphous shape via radial distances measurement, for the more diaphanous registers. The present methodology achieved a resolution of 10 μm/pixel. The algorithm of nonlinear elliptic fit with outliers rejection resulted a robust option for infrared reflex artifacts, whereas, radial distance measurement could lead us towards a new way of spatiotemporal analysis of pupillary dynamic.

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Section: B Digital Image Processingmentioning

confidence: 99%

“…Typically, this last task consists in some kind of filtering [10,12]. In this case, morphological operations was done (opening and close) [4].…”

Section: B Digital Image Processingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Approximations of Pupillary Shape in High-Definition Video-Oculography Registers

Mora-Martínez

Suaste-Gómez

2017

VII Latin American Congress on Biomedical Engineering CLAIB 2016, Bucaramanga, Santander, Colombia, October 26th -28th, 2016

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“…Since the accessible informational collection was little, part thickness estimation (KDE) of the certifiable and faker score appropriations of the preparation set are utilized to quantify execution of the BGM calculation. Fabiola M. Villalobos-Castaldi and Ernesto Suaste-Gómez [22] have proposed a novel pupillary based confirmation framework, alongside the early personality verification results and examination, in view of the spatio-transient highlights processed from the unconstrained pupillary motions. The creators exhibit that this biometric attribute has the ability to give enough discriminative data to validate the character of a subject.…”

Section: Related Workmentioning

confidence: 99%

A Novel Retinal Recognition System for Pathological Retina To Enhance Security

Rani¹,

Rani²

2018

IJET

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Biometric acknowledgment gives a characteristic and solid answer for the issue of individual distinguishing proof. One of the biometric ID framework utilized with high exactness is the retinal verification as a result of its many-sided quality in spoofing. However in these frameworks, acknowledgment rate is enormously influenced by the vasculature multifaceted nature of retinal images. This vascular example turns out to be exceptionally perplexing in sick retinal pictures because of the nearness of obsessive signs. In this manner, we require a computerized productive calculation which can evacuate these abnormalities before matching and decision making. The proposed novel hybrid clustering algorithm Adaptive Weighted Neighbour (AWN) Classification Algorithm classifies the input retinal image based on the features extracted and match the features with the trained features. The proposed feature vector consists of blood vessel structure, bifurcation points, bifurcation angles and vessel width. Results from the AWN are compared with state of the art classifier. It enables high security, good performance and greater accuracy. Also it provides better FAR, FRR and decreases the error rate.

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Iris Liveness Detection by Modeling Dynamic Pupil Features

Czajka

2016

Handbook of Iris Recognition

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A new spontaneous pupillary oscillation-based verification system

Cited by 23 publications

References 19 publications

Approximations of Pupillary Shape in High-Definition Video-Oculography Registers

Approximations of Pupillary Shape in High-Definition Video-Oculography Registers

A Novel Retinal Recognition System for Pathological Retina To Enhance Security

Iris Liveness Detection by Modeling Dynamic Pupil Features

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