ABSTRACT
Generally, the easiest way to withdraw money from your bank account is by using an Automated Teller Machine (ATM). The user can withdraw the money by inserting their card into the slot on the machine, and then entering a four-digit Personal Identification Number (PIN) to complete the transaction process. Similarly, some banks adopted the method of using a One Time Password (OTP) to complete the transaction process to make it more secure. With the recent advancements in technology, there are many new methods that can be used for withdrawing money from ATMs, like cardless cash withdrawal or using one's biometrics. But, due to the recent COVID-19 pandemic, we refrain from using things that are not sanitized properly. People started avoiding going to the ATMs since hygiene was a major concern during the pandemic. Also, due to the constant hand washing and the use of sanitizers, the use of conventional biometrics was not efficient. As a result, the idea of using a method that is contact-less and is also more secure emerged, i.e., the palm vein technology. The palm vein technology uses a person's vein pattern, which is unique to everyone and can help us achieve better results with greater accuracy. The paper proposes a concept of using a person's vein pattern as a method of contact-less authentication. It is an extremely safe verification procedure because no two people in the world, not even identical twins, can have the same palm vein structure or pattern. Additionally, it is more secure because it is nearly impossible to replicate the palm vein pattern. © 2022 IEEE.
ABSTRACT
Biometrics are the among most popular authentication methods due to their advantages over traditional methods, such as higher security, better accuracy and more convenience. The recent COVID-19 pandemic has led to the wide use of face masks, which greatly affects the traditional face recognition technology. The pandemic has also increased the focus on hygienic and contactless identity verification methods. The forearm is a new biometric that contains discriminative information. In this paper, we proposed a multimodal recognition method that combines the veins and geometry of a forearm. Five features are extracted from a forearm Near-Infrared (Near-Infrared) image: SURF, local line structures, global graph representations, forearm width feature and forearm boundary feature. These features are matched individually and then fused at the score level based on the Improved Analytic Hierarchy Process-entropy weight combination. Comprehensive experiments were carried out to evaluate the proposed recognition method and the fusion rule. The matching results showed that the proposed method can achieve a satisfactory performance. © 2022 The Authors. IET Biometrics published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
ABSTRACT
Biometrics are the among most popular authentication methods due to their advantages over traditional methods, such as higher security, better accuracy and more convenience. The recent COVID-19 pandemic has led to the wide use of face masks, which greatly affects the traditional face recognition technology. The pandemic has also increased the focus on hygienic and contactless identity verification methods. The forearm is a new biometric that contains discriminative information. In this paper, we proposed a multimodal recognition method that combines the veins and geometry of a forearm. Five features are extracted from a forearm Near-Infrared (Near-Infrared) image: SURF, local line structures, global graph representations, forearm width feature and forearm boundary feature. These features are matched individually and then fused at the score level based on the Improved Analytic Hierarchy Process-entropy weight combination. Comprehensive experiments were carried out to evaluate the proposed recognition method and the fusion rule. The matching results showed that the proposed method can achieve a satisfactory performance.