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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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Flowchart of the experimental procedure of our research.
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sensors-15-16866-f001: Flowchart of the experimental procedure of our research.

Mentions: An overview of the proposed method is shown in Figure 1. Because the input finger-vein image consists of two parts, i.e., the finger region containing the finger-vein information and the background region, the method to detect the finger region is first applied in order to remove the background, which contains unnecessary information. In the next step, based on the detected upper and lower finger boundaries detected in the previous step, the segmented finger region is stretched into a rectangular form in the normalization step. The processing time is reduced by obtaining a sub-sample of the stretched finger-vein image to reduce the size of the image. Before the recognition features are extracted, the quality of the finger-vein image is enhanced by using Gabor filtering, subsequent to which the preprocessed image is applied to the feature extraction step using the local binary pattern (LBP) method. In the next step, the hamming distance (HD) is calculated to determine the matching distance between the extracted code features of the input finger-vein image and the enrolled image. The input finger-vein image is then classified as either being genuine or being that of an imposter by using the enrolled data based on the matching distance.


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)

Flowchart of the experimental procedure of our research.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-16866-f001: Flowchart of the experimental procedure of our research.
Mentions: An overview of the proposed method is shown in Figure 1. Because the input finger-vein image consists of two parts, i.e., the finger region containing the finger-vein information and the background region, the method to detect the finger region is first applied in order to remove the background, which contains unnecessary information. In the next step, based on the detected upper and lower finger boundaries detected in the previous step, the segmented finger region is stretched into a rectangular form in the normalization step. The processing time is reduced by obtaining a sub-sample of the stretched finger-vein image to reduce the size of the image. Before the recognition features are extracted, the quality of the finger-vein image is enhanced by using Gabor filtering, subsequent to which the preprocessed image is applied to the feature extraction step using the local binary pattern (LBP) method. In the next step, the hamming distance (HD) is calculated to determine the matching distance between the extracted code features of the input finger-vein image and the enrolled image. The input finger-vein image is then classified as either being genuine or being that of an imposter by using the enrolled data based on the matching distance.

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