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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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Device for capturing finger-vein images for the second (mid-quality) database.
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sensors-15-16866-f008: Device for capturing finger-vein images for the second (mid-quality) database.

Mentions: In addition, we used two other databases, the first of which was constructed by selecting the vein images of six fingers among the images of 10 fingers in the database I (which were collected by the finger-vein capturing device without the guiding bar in previous research [7]). The device, which was used for collecting the database I [7], is shown in Figure 8. Because the guiding bar was absent, the misalignment among trial images of each finger in this database is relatively high; therefore, this was considered mid-quality database. In detail, each people puts his or her finger on the hole of the upper-part of device, and the size of the hole in the device for capturing the finger-vein image is fixed and limited in order to remove the effect by the environmental light into the captured image. Therefore, the part of finger area can be acquired in the image as shown in Figure 9a,b. Consequently, it is often the case that some part of the finger area (which is seen in the enrolled image) is not seen in the recognized image, which cannot be compensated by preprocessing step and can reduce the accuracy of recognition. In order to solve this problem, we propose a new device including two guiding bars for fingertip and side of finger as shown in Figure 7, which can make the consistent finger area be acquired by our device with reduced misalignment. However, no guiding bar is used in the other device of Figure 8, which is used for collecting the 2nd database. Therefore, we call the 1st and 2nd databases collected by the devices of Figure 7 and Figure 8 as good-quality and mid-quality databases, 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)

Device for capturing finger-vein images for the second (mid-quality) database.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-16866-f008: Device for capturing finger-vein images for the second (mid-quality) database.
Mentions: In addition, we used two other databases, the first of which was constructed by selecting the vein images of six fingers among the images of 10 fingers in the database I (which were collected by the finger-vein capturing device without the guiding bar in previous research [7]). The device, which was used for collecting the database I [7], is shown in Figure 8. Because the guiding bar was absent, the misalignment among trial images of each finger in this database is relatively high; therefore, this was considered mid-quality database. In detail, each people puts his or her finger on the hole of the upper-part of device, and the size of the hole in the device for capturing the finger-vein image is fixed and limited in order to remove the effect by the environmental light into the captured image. Therefore, the part of finger area can be acquired in the image as shown in Figure 9a,b. Consequently, it is often the case that some part of the finger area (which is seen in the enrolled image) is not seen in the recognized image, which cannot be compensated by preprocessing step and can reduce the accuracy of recognition. In order to solve this problem, we propose a new device including two guiding bars for fingertip and side of finger as shown in Figure 7, which can make the consistent finger area be acquired by our device with reduced misalignment. However, no guiding bar is used in the other device of Figure 8, which is used for collecting the 2nd database. Therefore, we call the 1st and 2nd databases collected by the devices of Figure 7 and Figure 8 as good-quality and mid-quality databases, 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