Limits...
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.

Show MeSH

Related in: MedlinePlus

Normalized finger-vein images and their average images when: (a) three images; and (b) five images were used for enrollment.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4541912&req=5

sensors-15-16866-f016: Normalized finger-vein images and their average images when: (a) three images; and (b) five images were used for enrollment.

Mentions: In this experiment, we used a number of input finger-vein images for enrollment instead of using only one image as was done previously [7,8,9,11,16,17,18,19,20,21,22,23,25]. The method involving the enrollment of finger-vein data using the average of multiple finger-vein images is as follows. After the input images were captured for enrollment, they were processed and normalized by the methods described in Section 2.2 and Section 2.3. From the image consisting of 50 × 20 pixels, obtained as a result of sub-sampling, we obtained the average image from which we extracted the LBP code which was then enrolled into the system. We applied this method by using either three or five enrollment finger-vein images to compare the matching accuracies with the conventional method, which only uses one image for enrollment. Examples of the average images generated from the 50 × 20 pixel images are shown in Figure 16. The experiments were conducted on the good-quality database as demonstrated in Figure 9a.


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)

Normalized finger-vein images and their average images when: (a) three images; and (b) five images were used for enrollment.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-16866-f016: Normalized finger-vein images and their average images when: (a) three images; and (b) five images were used for enrollment.
Mentions: In this experiment, we used a number of input finger-vein images for enrollment instead of using only one image as was done previously [7,8,9,11,16,17,18,19,20,21,22,23,25]. The method involving the enrollment of finger-vein data using the average of multiple finger-vein images is as follows. After the input images were captured for enrollment, they were processed and normalized by the methods described in Section 2.2 and Section 2.3. From the image consisting of 50 × 20 pixels, obtained as a result of sub-sampling, we obtained the average image from which we extracted the LBP code which was then enrolled into the system. We applied this method by using either three or five enrollment finger-vein images to compare the matching accuracies with the conventional method, which only uses one image for enrollment. Examples of the average images generated from the 50 × 20 pixel images are shown in Figure 16. The experiments were conducted on the good-quality database as demonstrated in Figure 9a.

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