Abstract: Spoof-detection and liveness analysis is performed using a software-based solution on a user device, such as a smartphone having a camera, audio output component (e.g., earpiece), and audio input component (e.g., microphone). One or more audio signals are emitted from the audio output component of the user device, reflect off a target, and are received back at the audio input component of the device. Based on the reflections, a determination is made as to whether the target is comprised of a three-dimensional face-like structure and/or face-like tissue. Using at least this determination, a finding is made as to whether the target is likely to be spoofed, rather than a legitimate, live person.

Abstract: Methods and systems for securing biometric templates and generating secret keys are provided. One or more images are received. Interest points are identified based on the received images, and a plurality of obfuscating data points are generated based on the interest points. An obfuscated template based on the interest points and the obfuscating data points is created and stored. A secret key can be encoded using a subset of at least one of the obfuscating data points and the interest points in the template.

Abstract: In a feature extraction and pattern matching system, image sharpening can enable vascular point detection (VPD) for detecting points of interest from visible vasculature of the eye. Pattern Histograms of Extended Multi-Radii Local Binary Patterns and/or Pattern Histograms of Extended Multi-Radii Center Symmetric Local Binary Patterns can provide description of portions of images surrounding a point of interest, and enrollment and verification templates can be generated using points detected via VPD and the corresponding descriptors. Inlier point pairs can be selected from the enrollment and verification templates, and a first match score indicating similarity of the two templates can be computed based on the number of inlier point pairs and one or more parameters of a transform selected by the inlier detection. A second match score can be computed by applying the selected transform, and either or both scores can be used to authenticate the user.

Abstract: In general, one aspect of the subject matter described in this specification can be embodied in methods that include obtaining one or more image regions from a first image of an eye. Each of the image regions may include a view of a respective portion of the white of the eye. The method may further include applying several distinct filters to each of the image regions to generate a plurality of respective descriptors for the region. The several distinct filters may include convolutional filters that are each configured to describe one or more aspects of an eye vasculature and in combination describe a visible eye vasculature in a feature space. A match score may be determined based on the generated descriptors and based on one or more descriptors associated with a second image of eye vasculature.

Abstract: In a feature extraction and pattern matching system, image sharpening can enable vascular point detection (VPD) for detecting points of interest from visible vasculature of the eye. Pattern Histograms of Extended Multi-Radii Local Binary Patterns and/or Pattern Histograms of Extended Multi-Radii Center Symmetric Local Binary Patterns can provide description of portions of images surrounding a point of interest, and enrollment and verification templates can be generated using points detected via VPD and the corresponding descriptors. Inlier point pairs can be selected from the enrollment and verification templates, and a first match score indicating similarity of the two templates can be computed based on the number of inlier point pairs and one or more parameters of a transform selected by the inlier detection. A second match score can be computed by applying the selected transform, and either or both scores can be used to authenticate the user.

Abstract: This specification describes technologies relating to biometric authentication based on images of the eye. In general, one aspect of the subject matter described in this specification can be embodied in methods that include obtaining images of a subject including a view of an eye. The methods may further include determining a behavioral metric based on detected movement of the eye as the eye appears in a plurality of the images, determining a spatial metric based on a distance from a sensor to a landmark that appears in a plurality of the images each having a different respective focus distance, and determining a reflectance metric based on detected changes in surface glare or specular reflection patterns on a surface of the eye.

Abstract: In a feature extraction and pattern matching system, image sharpening can enable vascular point detection (VPD) for detecting points of interest from visible vasculature of the eye. Pattern Histograms of Extended Multi-Radii Local Binary Patterns and/or Pattern Histograms of Extended Multi-Radii Center Symmetric Local Binary Patterns can provide description of portions of images surrounding a point of interest, and enrollment and verification templates can be generated using points detected via VPD and the corresponding descriptors. Inlier point pairs can be selected from the enrollment and verification templates, and a first match score indicating similarity of the two templates can be computed based on the number of inlier point pairs and one or more parameters of a transform selected by the inlier detection. A second match score can be computed by applying the selected transform, and either or both scores can be used to authenticate the user.

Abstract: In a feature extraction and pattern matching system, image sharpening can enable vascular point detection (VPD) for detecting points of interest from visible vasculature of the eye. Pattern Histograms of Extended Multi-Radii Local Binary Patterns and/or Pattern Histograms of Extended Multi-Radii Center Symmetric Local Binary Patterns can provide description of portions of images surrounding a point of interest, and enrollment and verification templates can be generated using points detected via VPD and the corresponding descriptors. Inlier point pairs can be selected from the enrollment and verification templates, and a first match score indicating similarity of the two templates can be computed based on the number of inlier point pairs and one or more parameters of a transform selected by the inlier detection. A second match score can be computed by applying the selected transform, and either or both scores can be used to authenticate the user.

Abstract: Systems and methods for electronically leashing a user to a mobile device. A user is authenticated on the mobile device and initial sensor data (e.g., radio signal readings, accelerometer readings, image/video, audio) is collected. Based on a timer or other triggering event, additional sensor data is captured and evaluated. Based on the evaluation of the sensor data, a value representing a likelihood of whether the device remains in possession of the user is determined. Upon determining that this value is less than a threshold, the user is required to reauthenticate on the mobile device to further engage with the device or particular features on the device.

Abstract: Methods and systems for securing biometric templates and generating secret keys are provided. One or more images are received. Interest points are identified based on the received images, and a plurality of obfuscating data points are generated based on the interest points. An obfuscated template based on the interest points and the obfuscating data points is created and stored. A secret key can be encoded using a subset of at least one of the obfuscating data points and the interest points in the template.

Abstract: An enrollment template can be a collection of interest points such as vascular points (VPD) and corresponding features such as Enhanced Multi-Radii Local Binary Patterns (EMR-LBP), Pattern Histograms of Enhanced Multi-Radii Local Binary Patterns (PH-EMR-LBP), Pattern histograms of Enhanced Multi-Radii Center-Symmetric Local Binary Patterns (PH-EMR-CS-LBP), and Enhanced Multi-Radii Center-Symmetric Local Binary Patterns (EMR-CS-LBP). In some implementations, an enrollment template can be created only if the acquired image exceeds a certain threshold based on ratio of VPD points to that of size of segmented scleral region. More than one enrollments are possible for a single user. Enrollment templates can be updated to accommodate behavioral and/or environmental variations affecting the acquired scans. Updating the enrollment templates using verification can be based on quality of a candidate verification template, match score, and/or other image and exposure similarity measures.

Abstract: Methods and systems for securing biometric templates and generating secret keys are provided. One or more images are received. Interest points are identified based on the received images, and a plurality of obfuscating data points are generated based on the interest points. An obfuscated template based on the interest points and the obfuscating data points is created and stored. A secret key can be encoded using a subset of at least one of the obfuscating data points and the interest points in the template.

Abstract: An enrollment template can be a collection of interest points such as vascular points (VPD) and corresponding features such as Enhanced Multi-Radii Local Binary Patterns (EMR-LBP), Pattern Histograms of Enhanced Multi-Radii Local Binary Patterns (PH-EMR-LBP), Pattern histograms of Enhanced Multi-Radii Center-Symmetric Local Binary Patterns (PH-EMR-CS-LBP), and Enhanced Multi-Radii Center-Symmetric Local Binary Patterns (EMR-CS-LBP). In some implementations, an enrollment template can be created only if the acquired image exceeds a certain threshold based on ratio of VPD points to that of size of segmented scleral region. More than one enrollments are possible for a single user. Enrollment templates can be updated to accommodate behavioral and/or environmental variations affecting the acquired scans. Updating the enrollment templates using verification can be based on quality of a candidate verification template, match score, and/or other image and exposure similarity measures.

Abstract: Methods and systems for securing biometric templates and generating secret keys are provided. One or more images are received. Interest points are identified based on the received images, and a plurality of obfuscating data points are generated based on the interest points. An obfuscated template based on the interest points and the obfuscating data points is created and stored. A secret key can be encoded using a subset of at least one of the obfuscating data points and the interest points in the template.