Biometric recognition refers to the automated recognition of individuals based on their
biological and behavioral characteristics such as fingerprint, face, iris, and voice. The first …

As of late, the need for biometric security framework is elevated for giving safety and security
against frauds, theft, and so on. Face recognition has gained a significant position among all …

Pushing by big data and deep convolutional neural network (CNN), the performance of face
recognition is becoming comparable to human. Using private large scale training datasets …

Low-light is an inescapable element of our daily surroundings that greatly affects the
efficiency of our vision. Research works on low-light imagery have seen a steady growth …

Micro-expressions are short, involuntary facial expressions which reveal hidden emotions.
Micro-expressions are important for understanding humans' deceitful behavior …

Local binary pattern (LBP) is a nonparametric descriptor, which efficiently summarizes the
local structures of images. In recent years, it has aroused increasing interest in many areas …

Facial expression recognition is to determine the emotional state of the face regardless of its
identity. Most of the existing datasets for facial expressions are captured in a visible light …

In recent years, heterogeneous face biometrics has attracted more attentions in the face
recognition community. After published in 2009, the HFB database [7] has been applied by …

Cross-modality face recognition is an emerging topic due to the wide-spread usage of
different sensors in day-to-day life applications. The development of face recognition …

Heterogeneous face recognition (HFR) involves matching two face images from alternate
imaging modalities, such as an infrared image to a photograph or a sketch to a photograph …