An Algorithm for Retina Features Extraction Based on Position of the Blood Vessel Bifurcation

Drozd, Radek; Hájek, Josef; Drahanský, Martin

doi:10.1007/978-3-642-35136-5_37

Cited by 3 publications

(3 citation statements)

References 3 publications

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“…Every individual has a unique, stable and impossible-to-replicate retinal pattern. Blood vessel patterns in the retina are not entirely inherited; for example, twins do not have the same blood vessel pattern and are less susceptible to external interference than the other biometrics 4 , 5 . Retinal biometrics are used in physical access entry applications requiring high security.…”

Section: Introductionmentioning

confidence: 99%

“…Blood vessel patterns in the retina are not entirely inherited; for example, twins do not have the same blood vessel pattern and are less susceptible to external interference than the other biometrics. 4,5 Retinal biometrics are used in physical access entry applications requiring high security. It also includes research and development facilities, military bases, and nuclear power plants.…”

Section: Introductionmentioning

confidence: 99%

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Human retinal biometric recognition system based on multiple feature extraction

Marappan

Murugesan²,

Malar

et al. 2023

J. Electron. Imag.

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Retinal biometric trait is one of the safest and most secure biometric traits that can be used for personal identification and authentication. The poor contrast in captured retinal images initially requires the adoption of a preprocessing technique, especially when the vessel segmentation is required. As a result, an effective preprocessing technique is employed before the feature extraction process. The reliability of the segmentation depends on the consistency of the contrast across the images. Due to the complexity of the retinal vascular patterns, segmenting the vessels manually is a time-consuming task that also requires extensive training and abilities to distinguish the thinner blood vessel pixels from the background of the retinal images. We present a unique blood vessel segmentation technique based on Radial Chebyshev Moments (RCMs) shape descriptors. Moment-based shape descriptors are typically strong, concise, and simple to compute. They are also insensitive to the object's scale, rotation, and translation. Furthermore, to eliminate the eye movement and to overcome the various lighting problems, the following multiple features are extracted in the feature extraction stage to accurately authenticate a person: statistical (gray-level) features, shape-based (RCM) features, and structural features, such as minutiae, bifurcation points, optical disc, and enclosed regions. The principal components analysis methodology is used to optimize the feature vector, and the target image is identified using the support vector machine classifier. This step helps to determine whether the test image belongs to the authorized person or not. RIDB and VARIA are the two standard retinal authentication databases and DRIVE and STARE are the two general retinal databases that are used for evaluating the performance of the system. The system yielded a high identification rate of 98%, 97.5%, 97.2% and 94.4% with average processing time of 0.987 s, 0.40 s, 1.262 s and 0.65 s, respectively. From the results, it is evident that the proposed method is more effective and efficient for authenticating individuals.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Human retinal biometric recognition system based on multiple feature extraction

Marappan

Murugesan²,

Malar

et al. 2023

J. Electron. Imag.

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“…Primary concentrate was on the precise extraction of veins [10]. Various techniques have been proposed for vein recognition and division for PC helped symptomatic framework to identify retinal illnesses, however their utilization for retinal recognizable proof is extremely uncommon [11]. The structure of the veins of the retina is exceptionally intricate [12].…”

Section: Introductionmentioning

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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Study of Feature Extraction of Retinal Scans

Abdulhamid

Muthomi

2019

Scientific Bulletin

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In this paper, the retina is discussed as part of the feature of extraction of retinal scans for use in security systems as a means of identification. The design system contains a method of image acquisition and processing of the image. A computer system is also incorporated for matching and verifying the image captured to an already present representation of unique features of the retina that are stored as templates for matching and identification. It should then either allow or deny the user depending on the results of the matching process. This paper shows the development of the step undertaken to process the image to the extraction of the features. The high resolution images are taken through a series of image enhancement process before feature extraction technics are applied and before templates are created for future referencing. The main limitation of this process is attributed to capturing the image from the retina. The image obtained may be of poor quality thus making the unique features of the retina unclear.

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An Algorithm for Retina Features Extraction Based on Position of the Blood Vessel Bifurcation

Cited by 3 publications

References 3 publications

Human retinal biometric recognition system based on multiple feature extraction

Human retinal biometric recognition system based on multiple feature extraction

A Novel Retinal Recognition System for Pathological Retina To Enhance Security

Study of Feature Extraction of Retinal Scans

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