The technology described in this document can be embodied in a method for preventing access to a secure system based on determining a captured image to be of an alternative representation of a live person. The method includes capturing an image of a subject illuminated by an infrared (IR) illumination source, and extracting, from the image, a portion representative of an iris of the subject. The method also includes determining that an amount of high-frequency features in the portion of the image satisfies a threshold condition indicative of the image being of an alternative representation of a live person, and in response, identifying the subject in the image to be an alternative representation of a live person. Responsive to identifying the subject in the image to be an alternative representation of a live person, the method further includes preventing access to the secure system.

To provide a technology of more accurately detecting spoofing in face authentication, without increasing a scale of a device configuration and a burden on a user. A spoofing detection device includes a facial image sequence acquisition unit, a line-of-sight change detection unit, a presentation information display unit, and a spoofing determination unit. The facial image sequence acquisition unit acquires a facial image sequence indicating the face of a user. The line-of-sight change detection unit detects information about a temporal change in the line-of-sight from the facial image sequence. The presentation information display unit displays presentation information presented to the user as part of an authentication process. The spoofing determination unit determines the likelihood of the face indicated by the facial image sequence being spoofing on the basis of the information about the temporal change in the line-of-sight with respect to the presentation information.

To provide a technology of more accurately detecting spoofing in face authentication, without increasing a scale of a device configuration and a burden on a user. A spoofing detection device includes a facial image sequence acquisition unit, a line-of-sight change detection unit, a presentation information display unit, and a spoofing determination unit. The facial image sequence acquisition unit acquires a facial image sequence indicating the face of a user. The line-of-sight change detection unit detects information about a temporal change in the line-of-sight from the facial image sequence. The presentation information display unit displays presentation information presented to the user as part of an authentication process. The spoofing determination unit determines the likelihood of the face indicated by the facial image sequence being spoofing on the basis of the information about the temporal change in the line-of-sight with respect to the presentation information.

Introduced here are approaches to authenticating the identity of speakers based on the “liveness” of the input. To prevent spoofing, an authentication platform may establish the likelihood that a voice sample represents a recording of word(s) uttered by a speaker whose identity is to be authenticated and then, based on the likelihood, determine whether to authenticate the speaker.

The present invention discloses system and method for fake face identification. The system is a multi-spectral sensing based bio-security system. The system uses CNN module along with thermal sensors to detect human face and also detects the human temperature. The system authenticates a human face and in case of temperature generates an alarm as an alert.

A computer-implemented method includes: (i) receiving location information that represents a physical location of a user; (ii) receiving a first image that has been captured by the user; (iii) in response to receiving the first image, obtaining a second image that has been captured by a camera and that depicts a particular object in an area around the physical location; (iv) determining whether the first image matches the second image; and (v) in response to determining that the first image matches the second image, determining that the user is authentic.

A computer-implemented method includes: (i) receiving location information that represents a physical location of a user; (ii) receiving a first image that has been captured by the user; (iii) in response to receiving the first image, obtaining a second image that has been captured by a camera and that depicts a particular object in an area around the physical location; (iv) determining whether the first image matches the second image; and (v) in response to determining that the first image matches the second image, determining that the user is authentic.

A system translates a first biometric template of a first type to enable comparison with a second biometric template of a second type. In one example, a canonical template structure to which the first and second biometric templates adhere may be identified and used to compare corresponding portions of the first and second biometric templates. In another example, types and associated formats of the first and second biometric templates may be identified to enable both to be translated to a general format that can then be compared. In still other examples, an identification system may use the first biometric template to determine an identity associated with first biometric data to either retrieve second stored biometric data associated with the identity of a same type as the second biometric template or verify that an account in an external system having a record storing the second biometric template is associated with the identity.

Facial recognition-based authentication comprises obtaining a first image of a target object, updating projection information associated with a display by a display device, obtaining a second image of the target object, the second image being an image of the target object after the projection information is updated, obtaining an image difference data based at least in part on the first image and the second image, and determining whether the target object is a virtual object based at least in part on the image difference data.

Exemplary embodiments of this disclosure provide a living body detection method and apparatus, an electronic device, a storage medium, and a payment system, a video surveillance system, and an access system to which the living body detection method is applied, and generally belong to the field of biometric recognition technologies. The living body detection method can include obtaining an image of a to-be-detected object performing key point detection on a biometric feature corresponding to the to-be-detected object in the image, and constructing a constraint box in the image according to detected key points. Further, the method can include capturing a shape change of the constraint box constructed in the image, and determining the to-be-detected object as a prosthesis in response to capturing an abnormal deformation of the constraint box or detecting no key points.