A Novel Authentication System Based on Hidden Biometric Trait

Kulkarni, Sujata; Raut, Ranjana; Dakhole, Pravin

doi:10.1016/j.procs.2016.05.229

Cited by 11 publications

(4 citation statements)

References 7 publications

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“…Image acquisition is the first basic step in FVR in which the finger vein image is captured by using NIR (near infra-red) light in the illumination transaction method. The acquisition device consists of an NIR assembly part for placement of the finger, and a charge-coupled device (CCD) preprocessor camera is then used to obtain an image of the finger vein [22,23]. The NIR light can pass through a finger but hemoglobin in the blood can absorb more NIR light than other tissues (such as bones and muscles) [9].…”

Section: Image Acquisitionmentioning

confidence: 99%

A Systematic Review of Finger Vein Recognition Techniques

Han-gang²,

et al. 2018

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Biometric identification is the study of physiological and behavioral attributes of an individual to overcome security problems. Finger vein recognition is a biometric technique used to analyze finger vein patterns of persons for proper authentication. This paper presents a detailed review on finger vein recognition algorithms. Such tools include image acquisition, preprocessing, feature extraction and matching methods to extract and analyze object patterns. In addition, we list some novel findings after the critical comparative analysis of the highlighted techniques. The comparative studies indicate that the accuracy of finger vein identification methods is up to the mark.

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Section: Image Acquisitionmentioning

confidence: 99%

A Systematic Review of Finger Vein Recognition Techniques

Han-gang²,

et al. 2018

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“…The effective blur radius of the Gaussian kernel depends on the value of σ as shown in (2). The σ in SUACE algorithm controls the resolution of the illumination map.…”

Section: Parameter Selectionmentioning

confidence: 99%

“…Superficial vein imaging becomes a mandatory requirement for numerous applications including phlebotomy, intravenous catheter insertion procedures, varicose vein treatments and vein pattern based biometric authentication systems [1], [2]. The light absorption property of hemoglobin allows infrared (IR) imaging techniques to reveal the superficial veins without using an invasive procedure [3].…”

Section: Introductionmentioning

confidence: 99%

Super-efficient spatially adaptive contrast enhancement algorithm for superficial vein imaging

Bandara

Rajarata

Giragama³

2017

2017 IEEE International Conference on Industrial and Information Systems (ICIIS)

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This paper presents a super-efficient spatially adaptive contrast enhancement algorithm for enhancing infrared (IR) radiation based superficial vein images in real-time. The super-efficiency permits the algorithm to run in consumer-grade handheld devices, which ultimately reduces the cost of vein imaging equipment. The proposed method utilizes the response from the low-frequency range of the IR image signal to adjust the boundaries of the reference dynamic range in a linear contrast stretching process with a tunable contrast enhancement parameter, as opposed to traditional approaches which use costly adaptive histogram equalization based methods. The algorithm has been implemented and deployed in a consumer grade Android-based mobile device to evaluate the performance. The results revealed that the proposed algorithm can process IR images of veins in real-time on low-performance computers. It was compared with several well-performed traditional methods and the results revealed that the new algorithm stands out with several beneficial features, namely, the fastest processing, the ability to enhance the desired details, the excellent illumination normalization capability and the ability to enhance details where the traditional methods failed.

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“…This method was based on artificial brain transformation. Kulkarni et al [24] applied a local binary pattern for authentication. Their method performs finger vein biometric identification.…”

Section: Introductionmentioning

confidence: 99%

Coronary Angiography Print: An Automated Accurate Hidden Biometric Method Based on Filtered Local Binary Pattern Using Coronary Angiography Images

Kobat

Tuncer

2021

JPM

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Background and purpose: Biometrics is a commonly studied research issue for both biomedical engineering and forensics sciences. Besides, the purpose of hidden biometrics is to discover hidden biometrics features. This work aims to demonstrate the biometric identification ability of coronary angiography images. Material and method: A new coronary angiography images database was collected to develop an automatic identification model. The used database was collected from 51 subjects and contains 2156 images. The developed model has to preprocess; feature generation using local binary pattern; feature selection with neighborhood component analysis; and classification phases. In the preprocessing phase; image rotations; median filter; Gaussian filter; and speckle noise addition functions have been used to generate filtered images. A multileveled extractor is presented using local binary pattern and maximum pooling together. The generated features are fed to neighborhood component analysis and the selected features are classified using k nearest neighbor classifier. Results: The presented angiography image identification method attained 99.86% classification accuracy on the collected database. Conclusion: The obtained findings demonstrate that the angiography images can be utilized as biometric identification. Moreover, we discover a new hidden biometric feature using coronary angiography images and name of this hidden biometric is coronary angiography print.

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A Novel Authentication System Based on Hidden Biometric Trait

Cited by 11 publications

References 7 publications

A Systematic Review of Finger Vein Recognition Techniques

A Systematic Review of Finger Vein Recognition Techniques

Super-efficient spatially adaptive contrast enhancement algorithm for superficial vein imaging

Coronary Angiography Print: An Automated Accurate Hidden Biometric Method Based on Filtered Local Binary Pattern Using Coronary Angiography Images

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