Face recognition frameworks are a part of facial image processing applications. [1] It has been a active research topic in the last two decades and its methods are presently sent in access control frameworks. It is the most common method for biometric distinguishing proof and has the advantage of non intrusiveness over the other biometric strategies, for example, irises and fingerprints. So the...

In the application of Biometric authentication, personal identification is regarded as an effective method for automatic recognition, with a high confidence, a person’s identity. Using multimodal biometric systems we typically get better performance compare to single biometric modality. This paper proposes the multimodal biometrics system for identity verification using two traits, i.e., speech...

Multimodal authentication systems represent an emerging trend for information security. These systems could replace conventional mono-modal biometric methods using two or more features for robust biometric authentication tasks. They employ unique combinations of measurable physical characteristics: fingerprint, facial features, iris of the eye, voice print, hand geometry, vein patterns, and so ...

The human hand possesses distinctive features which can reveal gender information. In addition, the hand is considered one of the primary biometric traits used to identify a person. In this work, we propose a large dataset of human hand images with detailed ground-truth information for gender recognition and biometric identification. The proposed dataset comprises of 11,076 hand images (dorsal ...

The verification of identity is becoming a crucial factor in our hugely interconnected society. Questions such as “Is she really who she claims to be?”, “Is this person authorized to use this facility?” are routinely being posed in a variety of scenarios ranging from issuing a driver’s license to gaining entry into a country. The necessity for reliable user authentication techniques has increas...

Biometric Authentication Protocols (BAPs) have increasingly been employed to guarantee reliable access control to places and services. However, it is well-known that biometric traits contain sensitive information of individuals and if compromised could lead to serious security and privacy breaches. Yasuda et al. [23] proposed a distributed privacy-preserving BAP which Abidin et al. [1] have sho...

In this paper, the authors present a multimodal biometric system using face and fingerprint features with the incorporation of Zernike Moment (ZM) and Radial Basis Function (RBF) Neural Network for personal authentication. It has been proven that face authentication is fast but not reliable while fingerprint authentication is reliable but inefficient in database retrieval. With regard to this f...

While multimodal biometric systems were commonly believed to be intrinsically more robust to spoof attacks than unimodal systems, recent results provided clear evidence that they can be evaded by spoofing a single biometric trait. This pointed out that also multimodal systems require specific anti-spoofing measures. In this chapter we introduce the issue of multimodal anti-spoofing, and give an...

Recognition of a person through his face is the primitive mean of human identification. Identifying a person through face biometric have grown its importance through the last decade and researchers have attempted to find unique facial feature-points. Facial data also contains change with expression and age, which makes recognition through face difficult. And there has developed a stringent nece...

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to u...