Non-contact finger vein acquisition system using NIR laser

Kim, Jiman; Kong, Hyoun‐Joong; Park, Sangyun; Noh, Samuel; Lee, Seung Rae; Kim, Taejeong; Kim, Hee Chan

doi:10.1117/12.810563

Cited by 18 publications

(22 citation statements)

References 9 publications

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“…X i(m,n,t)  X i(m × n, t) = X i (4) where X i(m,n,t) represents the decomposed dynamic NIR image of m×n×t (512×614×1200) dimensions. The temporal feature is extracted from the reconstructed dynamic NIR image, X i(m,n,t) via summation of NIR data across all m×n pixels at each time frame, or alternately selecting one of the m×n pixels and extracting its time series as follows:…”

Section: Dynamic Image Reconstructionmentioning

confidence: 99%

“…[1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] These studies use only spatial information of the measured NIR images in order to improve detection and localization of blood vessels and estimate useful anatomical information clinically. However, there has been no study that has focused on extracting both the spatial and temporal features of dynamic NIR images obtained via non-contact near-infrared optical scanner (NIROS) without the use of external contrast agents.…”

Section: Introductionmentioning

confidence: 99%

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Anatomical co-registration using spatio-temporal features of a non-contact near-infrared optical scanner

et al. 2014

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Non-contact based near-infrared (NIR) optical imaging devices are developed for non-invasive imaging of deep tissues in various clinical applications. Most of these devices focus on obtaining the spatial information for anatomical co-registration of blood vessels as in sub-surface vein localization applications. In the current study, the anatomical co-registration of blood vessels based on spatio-temporal features was performed using NIR optical imaging without the use of external contrast agents. A 710 nm LED source and a compact CCD camera system were employed during simple cuff (0 to 60 mmHg) experiment in order to acquire the dynamic NIR data from the dorsum of a hand. The spatio-temporal features of dynamic NIR data were extracted from the cuff experimental study to localize vessel according to blood dynamics. The blood vessels shape is currently reconstructed from the dynamic data based on spatio-temporal features. Demonstrating the spatio-temporal feature of blood dynamic imaging using a portable non-contact NIR imaging device without external contrast agents is significant for applications such as peripheral vascular diseases.

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Section: Dynamic Image Reconstructionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Anatomical co-registration using spatio-temporal features of a non-contact near-infrared optical scanner

et al. 2014

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“…The curvature ( κ ) was then calculated to determine the positions and widths of the veins from the local curvature maxima [7,10]. In this study, the one-dimensional curvature in a vertical direction was defined using Equation (1) to evaluate the vein images across the line segment quantitatively.…”

Section: Finger Vein Imagingmentioning

confidence: 99%

“…

κ = \frac{y^{″}}{{(1 + {(y^{'})}^{2})}^{1.5}},

where y is the light intensity, y ’ is its first derivative, and y ” is its second derivative. To evaluate the magnitude of the finger vein image quantitatively, a score (magnitudes of the finger vein, which is one of the performance indices in vein-pattern recognition) can be defined by Equation (2) [7,10]. …”

Section: Finger Vein Imagingmentioning

confidence: 99%

Imaging of the Finger Vein and Blood Flow for Anti-Spoofing Authentication Using a Laser and a MEMS Scanner

Lee

Moon

Lim

et al. 2017

Sensors

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A new authentication method employing a laser and a scanner is proposed to improve image contrast of the finger vein and to extract blood flow pattern for liveness detection. A micromirror reflects a laser beam and performs a uniform raster scan. Transmissive vein images were obtained, and compared with those of an LED. Blood flow patterns were also obtained based on speckle images in perfusion and occlusion. Curvature ratios of the finger vein and blood flow intensities were found to be nearly constant, regardless of the vein size, which validated the high repeatability of this scheme for identity authentication with anti-spoofing.

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“…Experimental results on small scale database using this technique has shown the good performance for biometric verification. In [4], finger vein sensor based on the laser illumination was introduced. Even though, the use of laser light source instead of LED will improve the quality of the finger vein imaging, it is highly sensitive to the back ground lighting that will introduce the additional challenges to achieve the accurate segmentation of the finger vein.…”

Section: Introductionmentioning

confidence: 99%

Novel finger vascular pattern imaging device for robust biometric verification

Ramachandra¹,

Surbiryala²,

Raja³

et al. 2014

2014 IEEE International Conference on Imaging Systems and Techniques (IST) Proceedings

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The vascular pattern of the finger has emerged as a promising new biometric modality, characterized by very low error rates, good spoofing resistance and user convenience when compared with other existing biometric modalities. In this paper, we present a new sensor design that is not only cost effective but also robust enough to capture the finger vascular (or finger vein) pattern. We evaluate the previously proposed finger vein verification approaches and also propose a new scheme that illustrates its superiority over existing approaches. Extensive experiments are carried out on the newly developed database constructed using our newly designed finger vein imaging sensor that comprises of 1780 finger vein samples corresponding to 89 unique fingers from 32 subjects. The data is collected in two different scenarios shows the efficacy of the proposed sensor as well as the proposed scheme.

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Non-contact finger vein acquisition system using NIR laser

Cited by 18 publications

References 9 publications

Anatomical co-registration using spatio-temporal features of a non-contact near-infrared optical scanner

Anatomical co-registration using spatio-temporal features of a non-contact near-infrared optical scanner

Imaging of the Finger Vein and Blood Flow for Anti-Spoofing Authentication Using a Laser and a MEMS Scanner

Novel finger vascular pattern imaging device for robust biometric verification

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