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Nonintrusive Finger-Vein Recognition System Using NIR Image Sensor and Accuracy Analyses According to Various Factors.

Pham TD, Park YH, Nguyen DT, Kwon SY, Park KR - Sensors (Basel) (2015)

Bottom Line: Therefore, fingerprint and iris recognitions are preferred alternatives.Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR) image sensor and analyze its accuracies considering various factors.The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands.

View Article: PubMed Central - PubMed

Affiliation: Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea. phamdanhtuyen@gmail.com.

ABSTRACT
Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR) image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands.

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Related in: MedlinePlus

Examples of input finger-vein images and finger-region detection results obtained with images from the three databases: Original images from the (a) good-quality; (c) mid-quality; and (e) open databases with their corresponding finger-region detection results shown in (b,d,f), respectively.
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sensors-15-16866-f002: Examples of input finger-vein images and finger-region detection results obtained with images from the three databases: Original images from the (a) good-quality; (c) mid-quality; and (e) open databases with their corresponding finger-region detection results shown in (b,d,f), respectively.

Mentions: As shown in Figure 2, a captured finger-vein image consists of the background surrounding the finger region, which contains the vein pattern, which is used for recognition purposes, and which has higher gray levels than the background. The background is removed from the captured image by detecting the four boundaries of the finger region consisting of the left and right boundaries in the horizontal direction, and upper and lower boundaries in the vertical direction, based on previous research [7]. In the images from the three databases, the left and right finger region boundaries are restricted by the size of the hole in the device for capturing the finger-vein image. Detailed explanations of the three databases and the device are provided in Section 3. As such, the values of XL and XR, which determine the left and right boundaries, as shown in Figure 2, are experimentally defined for the three databases. In the case of the good-quality database with 640 × 480 pixel images, the values of XL and XR are 180 and 480 pixels, respectively. For the mid-quality database with the same image size, the values of XL and XR are 220 and 470 pixels, respectively. The third (open) database, which consists of images with a size of 320 × 240 pixels, XL and XR are 20 and 268 pixels, respectively.


Nonintrusive Finger-Vein Recognition System Using NIR Image Sensor and Accuracy Analyses According to Various Factors.

Pham TD, Park YH, Nguyen DT, Kwon SY, Park KR - Sensors (Basel) (2015)

Examples of input finger-vein images and finger-region detection results obtained with images from the three databases: Original images from the (a) good-quality; (c) mid-quality; and (e) open databases with their corresponding finger-region detection results shown in (b,d,f), respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541912&req=5

sensors-15-16866-f002: Examples of input finger-vein images and finger-region detection results obtained with images from the three databases: Original images from the (a) good-quality; (c) mid-quality; and (e) open databases with their corresponding finger-region detection results shown in (b,d,f), respectively.
Mentions: As shown in Figure 2, a captured finger-vein image consists of the background surrounding the finger region, which contains the vein pattern, which is used for recognition purposes, and which has higher gray levels than the background. The background is removed from the captured image by detecting the four boundaries of the finger region consisting of the left and right boundaries in the horizontal direction, and upper and lower boundaries in the vertical direction, based on previous research [7]. In the images from the three databases, the left and right finger region boundaries are restricted by the size of the hole in the device for capturing the finger-vein image. Detailed explanations of the three databases and the device are provided in Section 3. As such, the values of XL and XR, which determine the left and right boundaries, as shown in Figure 2, are experimentally defined for the three databases. In the case of the good-quality database with 640 × 480 pixel images, the values of XL and XR are 180 and 480 pixels, respectively. For the mid-quality database with the same image size, the values of XL and XR are 220 and 470 pixels, respectively. The third (open) database, which consists of images with a size of 320 × 240 pixels, XL and XR are 20 and 268 pixels, respectively.

Bottom Line: Therefore, fingerprint and iris recognitions are preferred alternatives.Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR) image sensor and analyze its accuracies considering various factors.The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands.

View Article: PubMed Central - PubMed

Affiliation: Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea. phamdanhtuyen@gmail.com.

ABSTRACT
Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR) image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands.

Show MeSH
Related in: MedlinePlus