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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

Matching distance distributions of authentic and imposter tests using (a) three images; and (b) five images for enrollment methods.
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sensors-15-16866-f019: Matching distance distributions of authentic and imposter tests using (a) three images; and (b) five images for enrollment methods.

Mentions: The experimental results of the methods in which three and five images were used for enrollment, are compared with those obtained by the conventional method (using one image for enrollment) in Table 4, where it can be seen that the matching accuracy was enhanced by increasing the number of enrollment images, in terms of low EER and high d-prime values. The ROC curves and the distribution plots of authentic and imposter tests corresponding to the results in Table 4 are shown in Figure 18 and Figure 19, respectively, and can be explained as follows. In the finger-vein database, matching errors were mostly caused by misalignment at the time when the input finger-vein images were initially recorded, which subsequently resulted in translation errors in the normalized images of 50 × 20 pixels. The use of image averaging reduced the translation errors within the normalized images and increased the similarities between the enrolled and the matched finger-vein data. Table 5 shows examples of error cases resulting in false rejection when the enrolled images were compared with the test image in the same class, listed according to the number of images used for enrollment.


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)

Matching distance distributions of authentic and imposter tests using (a) three images; and (b) five images for enrollment methods.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-16866-f019: Matching distance distributions of authentic and imposter tests using (a) three images; and (b) five images for enrollment methods.
Mentions: The experimental results of the methods in which three and five images were used for enrollment, are compared with those obtained by the conventional method (using one image for enrollment) in Table 4, where it can be seen that the matching accuracy was enhanced by increasing the number of enrollment images, in terms of low EER and high d-prime values. The ROC curves and the distribution plots of authentic and imposter tests corresponding to the results in Table 4 are shown in Figure 18 and Figure 19, respectively, and can be explained as follows. In the finger-vein database, matching errors were mostly caused by misalignment at the time when the input finger-vein images were initially recorded, which subsequently resulted in translation errors in the normalized images of 50 × 20 pixels. The use of image averaging reduced the translation errors within the normalized images and increased the similarities between the enrolled and the matched finger-vein data. Table 5 shows examples of error cases resulting in false rejection when the enrolled images were compared with the test image in the same class, listed according to the number of images used for enrollment.

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