Feature point validation for improved retina recognition

Fatima, Joddat; Syed, Adeel M.; Akram, M. Usman

doi:10.1109/bioms.2013.6656142

Cited by 6 publications

(6 citation statements)

References 13 publications

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“…In [24], the authors affirm that ending points and bifurcations are the key of retina recognition. However, there are certain vascular structures which contain invalid bifurcation and ending.…”

Section: Retinal Images In Biometricsmentioning

confidence: 93%

“…the vessel tree is considered as unique component which is used to authentication [21,16,23]. Other works extract bifurcations and ending points from blood vessels which are considered as personal unique features [19,24]. To avoid noising and difference between segmentation methods, several methods proceed to thinning vessels before extracting biometry features, in order to preserve only main vessels [24,23].…”

Section: 5 Conclusionmentioning

confidence: 99%

“…Others works aim to filter bifurcation and ending points to ensure a performant identification process [24].…”

Section: 5 Conclusionmentioning

confidence: 99%

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Retinal Image Processing in Biometrics

Kachouri

Akil

Elloumi

2019

Series in BioEngineering

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In this chapter, retinal image processing will be addressed as a Hidden Biometric modality. Considered as safe modalities, the retinal vascular network provide a unique pattern for each individual since it does not change throughout the life of the person. In addition, the retina offers a high level of recognition, which makes it suitable for high security applications thanks to its universality, its invariability over time and its difficulty to falsify.

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Section: Retinal Images In Biometricsmentioning

confidence: 93%

Section: 5 Conclusionmentioning

confidence: 99%

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Retinal Image Processing in Biometrics

Kachouri

Akil

Elloumi

2019

Series in BioEngineering

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“…The application of the proposed method is not limited to medical use only, as there are other applications that use retinal blood vessel segmentation as well (e.g. biometrics [4], [8], [11]). This paper is structured as follows.…”

Section: Introductionmentioning

confidence: 99%

Retinal blood vessel segmentation based on heuristic image analysis

2019

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Automatic analysis of retinal fundus images is becoming increasingly present today, and diseases such as diabetic retinopathy and age-related macular degeneration are getting a higher chance of being discovered in the early stages of their development. In order to focus on discovering those diseases, researchers commonly preprocess retinal fundus images in order to detect the retinal landmarks -blood vessels, fovea and the optic disk. A large number of methods for the automatic detection of retinal blood vessels from retinal fundus images already exists, but many of them are using unnecessarily complicated approaches. In this paper we demonstrate that a reliable retinal blood vessel segmentation can be achieved with a cascade of very simple image processing methods. The proposed method puts higher emphasis on high specificity (i.e. high probability that the segmented pixels actually belong to retinal blood vessels and are not false positive detections) rather than on high sensitivity. The proposed method is based on heuristically determined parametric edge detection and shape analysis, and is evaluated on the publicly available DRIVE and STARE datasets on which it achieved the average accuracy of 96.33% and 96.10%, respectively.

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“…According to (Fatima, Syed, & Akram, 2013), those features are removed using a windowing technique on the skeleton vascular pattern. It has achieved a reduction factor of 94.74% for raw images and 90.96% for processed images.…”

Section: ) Eye Based Featuresmentioning

confidence: 99%

Authentication systems: principles and threats

Abdulkader¹,

Atia²,

Mostafa³

2015

CIS

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Identity manipulation is considered a serious security issue that has been enlarged with the spread of automated systems that could be accessed either locally or remotely. Availability, integrity, and confidentiality represent the basic requirements that should be granted for successful authentication systems. Personality verification has taken multiple forms depending on different possession types. They are divided into knowledge based, token based, and biometric based authentication. The permanent ownership to the human being has increased the chances of deploying biometrics based authentication in highly secure systems. It includes capturing the biological traits, which are physiological or behavioral, extracting the important features and comparing them to the previously stored features that belong to the claimed user. Various kinds of attacks aim to take down the basic requirements at multiple points. This paper describes different types of authentication along with their vulnerable points and threatening attacks. Then it provides more details about the biometric system structure as well as examples of distinguishing biological characteristics, organized by their locations. It shows the performance results of various biometric systems along with the deployed algorithms for different components.

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Feature point validation for improved retina recognition

Cited by 6 publications

References 13 publications

Retinal Image Processing in Biometrics

Retinal Image Processing in Biometrics

Retinal blood vessel segmentation based on heuristic image analysis

Authentication systems: principles and threats

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