Feature extraction of finger-vein patterns based on repeated line tracking and its application to personal identification

Miura, Naoto; Nagasaka, Akio; Miyatake, Takafumi

doi:10.1007/s00138-004-0149-2

Cited by 681 publications

(503 citation statements)

References 9 publications

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“…This paper presents a Kinect-based acquisition method of hand vein, also introduces template matching based on relevance and improved two image extraction methods of reference [5]. Firstly ,use Kinect to capture images; Secondly, extract the effective area of the hand vein, images can be extracted directly when using the template matching method, but the opisthenar contour needs to be extracted and the distance from each contour point to the center of opisthenar calculated before when choosing the second extraction method, determine the location of the second and fourth finger web, then intercept effective area; finally, threshold preprocess the obtain images, then get final image by median filtering .…”

Section: Resultsmentioning

confidence: 99%

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Kinect's Opisthenar Vein Image Acquisition Method

Zixiang¹,

Yongxiu²

2016

Proceedings of the 2015 2nd International Forum on Electrical Engineering and Automation (IFEEA 2015)

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Abstract.Although the current opisthenar vein image acquisition is less demanding, but practical applications often require special equipment, this paper describes a theme based on Microsoft Kinect sensors opisthenar vein acquisition. Using Microsoft's Kinect sensor to collect the opisthenar vein image, introducing correlation-based template matching and ROI two extraction algorithms to get the effective area, after processing, to give a clear opisthenar vein image. Inspection of the acquired image under Matlab environment proves it to be a quick,simple, and easy to implement solution.

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Section: Resultsmentioning

confidence: 99%

“…This paper provides two methods to locate extract the hand vein area, one is based on the relevant template matching, and the other is advanced ROI [5] extraction algorithm. Two algorithms will be introduced as follows.…”

Section: Effective Vein Region Extractionmentioning

confidence: 99%

Kinect's Opisthenar Vein Image Acquisition Method

Zixiang¹,

Yongxiu²

2016

Proceedings of the 2015 2nd International Forum on Electrical Engineering and Automation (IFEEA 2015)

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“…A finger knuckle is also expected to be distinctive as well as a fingerprint and a palmprint, although statistical analysis using a huge dataset has to be required to demonstrate the uniqueness of finger knuckle patterns 37) . 43) and finger vein 44) . Recently, the international competition of finger vein recognition * has been held in conjunction with International Conference on Biometrics.…”

Section: Hand-based Biometricsmentioning

confidence: 98%

[Invited Paper] Recent Advances in Biometric Recognition

Ito

Aoki

2018

MTA

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This paper presents recent advances in biometric recognition, where we focus on face, fingerprint and iris recognition, which are major research topics on biometric recognition. We summarize the research trend of face, fingerprint and iris recognition over the past decade. This paper also presents our activities of biometric recognition. Our approach employs the phase information obtained by Discrete Fourier Transform (DFT) of images. The phase information preserves the inherent features of the image, and its correlation function, called phase correlation or Phase-Only Correlation (POC), gives us both the good similarity measure for biometric recognition and the translational displacement for image registration.Our approach of using phase information has been successfully applied to fingerprint, face, iris, palmprint, finger knuckle and dental recognition. Among them, we present some interesting results of palmprint recognition, finger knuckle recognition and dental recognition.

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“…They systematically developed an original method for the finger-vein feature extraction using Gabor filters. Miural et all in 2011 [13] used repeated line racking to tract the local dark position of image but it was difficult to define a shape for variable width veins. While Cho et al in 2011 [14] used an adaptive version of Gabor filter to enhance the distinctiveness region in the original finger vein image.…”

Section: Related Workmentioning

confidence: 99%

A Novel Approach for Finger Vein Pattern Enhancement using Gabor and Canny Edge Detector

Akintoye¹,

Shafry²,

Abdullah³

2017

IJCA

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Biometrics is the science of identifying a person using physiological or behavioural features. A biometric verification system authenticates an individual's identity by matching the live biometric template to his/her biometric template or templates stored in the system database. Nevertheless, finger vein verification system is cost effective in comparison but high in accuracy with opportunities of fake detection and biocryptography system. Previous research on finger vein verification has proved that it's accuracy relies on enhancement of vein image pattern quality. However, at times noise generates as a result of hair and skin texture, which is as well enhanced because they are much resembles the vein structure. Noise is any process that affects the original image since it is not part of the original image. This causes great error when extracting accurate vein patterns. It also leads to increasing processing time during finger vein extraction, which is eventually cause an inaccuracy in matching/verification system. To overcome this problem, a novel approach for finger vein pattern enhancement using Gabor-Canny edge detector is proposed, which is far better and more accurate than previous method.

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Feature extraction of finger-vein patterns based on repeated line tracking and its application to personal identification

Cited by 681 publications

References 9 publications

Kinect's Opisthenar Vein Image Acquisition Method

Kinect's Opisthenar Vein Image Acquisition Method

[Invited Paper] Recent Advances in Biometric Recognition

A Novel Approach for Finger Vein Pattern Enhancement using Gabor and Canny Edge Detector

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