A dermatoglyph detector includes a detection circuit and an electronic processor unit. The detection circuit includes an electrically conductive thin film in which there are formed both electrodes that are arranged to come into contact with the skin of a portion of a human body and also conductive tracks connecting the electrodes to the processor unit. The processor unit is arranged to determine electrical characteristics of the body portion extending between each pair of electrodes in contact with the skin, and to execute a computer program for acting on the basis of the determined electrical characteristics to distinguish between an authentic body portion and a fake body portion. The detection circuit includes at least two track segments of different shapes between two calibration terminals so as to present an impedance ratio that is not equal to unity.

In implementations of the subject matter as described herein, there is provided a method for forgery detection of a face image. Subsequent to inputting a face image, it is detected whether a blending boundary due to the blend of different images exists in the face image, and then a corresponding grayscale image is generated based on a result of the detection, where the generated grayscale image can reveal whether the input face image is formed by blending different images. If a visible boundary corresponding to the blending boundary exists in the generated grayscale image, it indicates that the face image is a forged image; on the contrary, if the visible boundary does not exist in the generated grayscale image, it indicates that the face image is a real image.

In implementations of the subject matter as described herein, there is provided a method for forgery detection of a face image. Subsequent to inputting a face image, it is detected whether a blending boundary due to the blend of different images exists in the face image, and then a corresponding grayscale image is generated based on a result of the detection, where the generated grayscale image can reveal whether the input face image is formed by blending different images. If a visible boundary corresponding to the blending boundary exists in the generated grayscale image, it indicates that the face image is a forged image; on the contrary, if the visible boundary does not exist in the generated grayscale image, it indicates that the face image is a real image.

A method for authenticating a user includes: an application frontend of a face recognition application, upon receipt of a face recognition request from an application backend of the face recognition application, causes a terminal device to activate a camera of the terminal device; the application frontend receives a video stream of a face of the user captured by the camera of the terminal device; the application frontend transmits the received video stream to the application backend; the application backend, upon receipt of the video stream, extracts a face characteristic of the user from the received video stream in real-time; and the application backend compares the extracted face characteristic with a stored reference face characteristic of the user and authenticates the user based on the extracted face characteristic matching the stored reference face characteristic.

Provided are methodology and system countering fraudulent document and/or image use when authentication of a transaction based on a given document or image use is required. Additionally provided is a manner of machine learning adapting the methodology for implementation thereof.

Various embodiments provide systems and methods for detecting tampering with a monitoring device using biometric data.

Face recognition systems are vulnerable to the presentation of spoofed faces, which may be presented to face recognition systems, for example, by an unauthorized user seeking to gain access to a protected resource. A face liveness detection method that addresses this vulnerability utilizes motion analysis to compare the relative movement among three regions of interest in a facial image and based upon that comparison to make a face liveness determination.

Biometrics are increasingly used to provide authentication and/or verification of a user in many security and financial applications for example. However, “spoof attacks” through presentation of biometric artefacts that are “false” allow attackers to fool these biometric verification systems. Accordingly, it would be beneficial to further differentiate the acquired biometric characteristics into feature spaces relating to live and non-living biometrics to prevent non-living biometric credentials triggering biometric verification. The inventors have established a variety of “liveness” detection methodologies which can block either low complexity spoofs or more advanced spoofs. Such techniques may provide for monitoring of responses to challenges discretely or in combination with additional aspects such as the timing of user's responses, depth detection within acquired images, comparison of other images from other cameras with database data etc.

A detection device includes a processing circuit that is configured to acquire an imaging video of a user to be authenticated, specify categories of micro-expressions of the user using the acquired imaging video, and determine whether an appearance pattern of each specified category for the micro-expressions is normal.

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.