What is face liveness detection?
What is liveness detection? Facial liveness detection’s biometrics refers to the use of computer vision technology to detect the harmless presence of a live user, rather than a representation such as a picture, a fake video or a mask.
Why is liveness detected?
Liveness Detection is needed to secure biometric authentication systems from fraud. For instance, a fraudster could use a photo, video or mask to attack a facial recognition algorithm and get unauthorized access to accounts or data.
What is passive liveness detection?
SAFR’s passive liveness detection enhances security for face biometric authentication solutions. It adds detection and alerting capabilities when a printed photo or digital image or video is presented for identity authentication or physical access control workflows.
Which sensor is used for face recognition?
Using infrared sensor technology for face recognition and human identification. Recent research has demonstrated distinct advantages using thermal infrared imaging for improving face recognition performance.
What does the term biometric spoofing mean?
Fake fingerprints aren’t difficult to make, but they are difficult to use. In biometric identification terminology, “spoofing” is the process of presenting a fake biometric (e.g. gummy fingerprint) to a system in order to gain access.
What is LBPH algorithm?
LBPH (Local Binary Pattern Histogram) is a Face-Recognition algorithm it is used to recognize the face of a person. It is known for its performance and how it is able to recognize the face of a person from both front face and side face.
What is Fisherface algorithm?
Fisherface is one of the popular algorithms used in face recognition, and is widely believed to be superior to other techniques, such as eigenface because of the effort to maximize the separation between classes in the training process.
Can fingerprints be spoofed?
Fingerprint spoofing is a way to circumvent the security of a biometric fingerprint system with the use of artificial fingerprints created using different materials and methods. To create a fingerprint spoof, the attacker should have access to fingerprints of a user who is already registered on the target system.
Can biometric data be faked?
Researchers have used a neural network to generate artificial fingerprints that work as a “master key” for biometric identification systems and prove fake fingerprints can be created.
What algorithms are used for facial recognition?
There are different types of face recognition algorithms, for example:
- Eigenfaces (1991)
- Local Binary Patterns Histograms (LBPH) (1996)
- Fisherfaces (1997)
- Scale Invariant Feature Transform (SIFT) (1999)
- Speed Up Robust Features (SURF) (2006)
What is PCA algorithm for face recognition?
PCA is a statistical approach used for reducing the number of variables in face recognition. In PCA, every image in the training set is represented as a linear combination of weighted eigenvectors called eigenfaces. These eigenvectors are obtained from covariance matrix of a training image set.