A finger vein recognition system

Sapkale, Manisha; Rajbhoj, S. M.

doi:10.1109/casp.2016.7746185

Cited by 13 publications

(3 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach is less sensitive to noise and makes use of the entire network. Cihui Xie et al [4], has demonstrated that the Convolutional Neural Network (CNN) is remarkably capable of learning biometric features that provide reliable and accurate matching. This paper presents a novel method for authenticating finger veins using CNN and supervised discrete hashing.…”

Section: Literature Reviewmentioning

confidence: 99%

Enhancing Security Within Restricted Hospital Zones by Integrating Finger Vein Authentication

Mathumitha Jeyashri. J,

Swetha. S,

Vishwa. J

et al. 2024

Int Res J Adv Engg Hub

View full text Add to dashboard Cite

The integration of finger vein authentication technology to enhance security measures within restricted zones in hospital environments, is the aim of this project. An advanced biometric technique called finger vein authentication uses each person's individual vein patterns to confirm their identification. It is especially desirable for applications where security is critical, such financial transactions, healthcare, and access control, because it provides a very safe and non-intrusive means of authentication. Although there has been considerable success with traditional finger vein authentication methods, deep learning techniques have completely changed this field. A branch of artificial intelligence called deep learning has shown impressive results in pattern recognition and picture analysis, which makes it a prime contender for improving the precision and dependability of finger vein authentication systems. Finger vein authentication utilizes biometric characteristics unique to everyone, providing a highly secure method of identity verification. By implementing this technology, hospitals can bolster access control, prevent unauthorized entry into sensitive areas, and safeguard patient information and critical resources. The project aims to implement finger vein authentication systems to regulate access to restricted areas such as operating rooms, medication storage areas, and patient information sections. Authorized personnel will undergo authentication via finger vein scans for entry, ensuring that only authorized individuals can access these zones.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Enhancing Security Within Restricted Hospital Zones by Integrating Finger Vein Authentication

Mathumitha Jeyashri. J,

Swetha. S,

Vishwa. J

et al. 2024

Int Res J Adv Engg Hub

View full text Add to dashboard Cite

show abstract

“…We need to count the pixel coincidence rate between the template image and the image to be matched. If this coincidence rate is greater than 25%, and the global feature difference between the two images does not exceed 0.0055, we have reason to believe that the two images originate from the same user, Otherwise the match fails [8].…”

Section: Decryption and Authenticationmentioning

confidence: 99%

Identification System Based on Fingerprint and Finger Vein

Wang

Hou

Wang

et al. 2020

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

In recent years, with the rapid development of information technology, more and more attention has been paid to information security. Biometrics is an important way to ensure information security, and digital vein recognition is an important branch of biometrics, which has an irreplaceable position in the field of information security. However, the traditional finger vein recognition is vulnerable to attacks such as replay, template tampering, and forging original features, which leads to the destruction of the authentication system. This paper proposes a solution to encrypt the feature points of finger vein with the key generated by the relative difference of fingerprint detail points based on the SM4 algorithm to realize the double encryption authentication of user information, so as to improve the security and accuracy of user identity identification and meet the increasing requirements of high security.

show abstract

“…el. [14] proposed an embedded finger vein recognition and classification system for human authentication. The proposed system based on a novel finger vein image recognition system.…”

Section: Introductionmentioning

confidence: 99%

Double stages of feature extarction-based GFPMI for colored finger vein identification

Sulaiman

Abdulazeez

Haron

2020

IJEECS

View full text Add to dashboard Cite

Today, finger vein recognition has a lot of attention as a promising approach of biometric identification framework and still does not meet the challenges of the researchers on this filed. To solve this problem, we propose s double stage of feature extraction schemes based localized finger fine image detection. We propose Globalized Features Pattern Map Indication (GFPMI) to extract the globalized finger vein line features basede on using two generated vein image datasets: original gray level color, globalized finger vein line feature, original localized gray level image, and the colored localized finger vein images. Then, two kinds of features (gray scale and texture features) are extracted, which tell the structure information of the whole finger vein pattern in the whole dataset. The recurrent based residual neural network (RNN) is used to identify the finger vein images. The experimental show that the localized colored finger vein images based globalized feature extraction has achieved the higher accuracy (93.49%) while the original image dataset achieved less accuracy by (69.86%).

show abstract

A finger vein recognition system

Cited by 13 publications

References 10 publications

Enhancing Security Within Restricted Hospital Zones by Integrating Finger Vein Authentication

Enhancing Security Within Restricted Hospital Zones by Integrating Finger Vein Authentication

Identification System Based on Fingerprint and Finger Vein

Double stages of feature extarction-based GFPMI for colored finger vein identification

Contact Info

Product

Resources

About