Eyeverify Inc.

Advanced New Technologies Co., Ltd.

Alibaba Group Holding Limited

Jumio Corporation

Yash Joshi

Reza R Derakhshani

Srikanth Parupati

Matthew Barrow

Vikas Gottemukkula

Sashi Kanth Saripalle

Zikomo Fields

Tetyana Anisimova

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.

Spoof detection using iris images

A method for detecting adverse conditions associated with a device includes receiving, at one or more processing devices at one or more locations, one or more image frames; receiving a set of signals representing outputs of one or more sensors of a device; estimating, based on the one or more image frames, a first set of one or more motion values; estimating, based on the set of signals, a second set of one or more motion values; determining that a degree of correlation between (i) a first motion represented by the first set of one or more motion values and (ii) a second motion represented by the second set of one or more motion values fails to satisfy a threshold condition; and in response to determining that the degree of correlation fails to satisfy the threshold condition, determining presence of an adverse condition associated with the device.

Multi-sensor motion analysis to check camera pipeline integrity

An adaptive spoofing method includes: causing a first display device to display a spoof representation of a human user; and obtaining multiple images of the spoof representation. The multiple images are captured automatically by an image capture device, each of the multiple images captures a different corresponding configuration of the spoof representation displayed on the first display device. The method also includes: executing a biometric authentication process separately on each of at least a subset of the multiple images; determining that the biometric authentication process authenticates the human user based on at least a first image from the subset; and identifying a configuration of the spoof representation corresponding to the first image as a failure condition associated with the biometric authentication process.

Automated adaptive displayed spoofing

An adaptive spoofing method includes obtaining multiple images of a spoof representation of a human user. The multiple images are captured automatically by an image capture device, and each of the multiple images is captured at a different relative position between the image capture device and the spoof representation. The method also includes: executing a biometric authentication process separately on each of at least a subset of the multiple images; determining that the biometric authentication process authenticates the human user based on at least a first image from the subset; and identifying a relative position between the image capture device and the spoof representation corresponding to the first image as a failure condition associated with the biometric authentication process.

Automated positional adaptive spoofing

An image transformation method includes: causing a first display device to display one or more calibration patterns. One or more first images include a corresponding calibration pattern of the one or more calibration patterns. The one or more first images are captured by an image capture device disposed at a non-zero capture angle with respect to the first display device. The method also includes determining based on the one or more first images, a transformation to be applied to account for the non-zero capture angle; obtaining a second image of a human user; applying the transformation to the second image to generate a transformed spoof representation of the human user for capture by the image capture device being held at the non-zero capture angle with respect to the first display device; and causing the first display device to display the transformed spoof representation.

Automated spoofing transformation

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for red eye detection are provided. In one aspect, a system includes an image acquisition device, first and second illuminators, and at least one processor. The first illuminator is arranged closer to the image acquisition device than the second illuminator. The image acquisition device is configured to capture a first facial image of a face of a subject with the first illuminator being on and the second illuminator being off and a second facial image of the face of the subject with the second illuminator being on and the first illuminator being off. The processor can process the first facial image based on the second facial image to determine whether at least one eye of the subject is live by determining that the first facial image includes a red eye reflection from the at least one eye.

Spoof detection based on red-eye effects

Technology described herein 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 a first image and a second image of a subject illuminated by electromagnetic radiation in a first and a second wavelength ranges, respectively. The method also includes extracting, from the first image, a first portion representative of a sclera region of the subject, and from the second image, a second portion representative of the same region. It is determined that each of the first portion and the second portion includes features representative of vasculature in the sclera region, and in response, the subject in the image is identified to be an alternative representation of a live person. Upon search identification, the method includes preventing access to the secure system.

Spoof detection by comparing images captured using visible-range and infrared (IR) illuminations

Methods, systems, and apparatus, including computer programs encoded on computer-readable storage media, are provided. In one aspect, a first image of an eye region of a subject is received, the first image captured under illumination by electromagnetic radiation having a wavelength in the 850 nm-1100 nm range. Based on the first image, a metric indicative of differential absorption of the electromagnetic radiation by an iris of the subject and a sclera of the subject is determined. It is identified, based on the metric, that the subject is a spoof representation of a human. Responsive to identifying that the subject is a spoof representation of a human, access to a secure system is prevented.

Infrared-based spoof detection

This document described a method that includes illuminating a first subject with electromagnetic radiation in a first wavelength range, and capturing a first image of the first subject under illumination of the first wavelength range. The method also includes illuminating the first subject with electromagnetic radiation in a second wavelength range, wherein a difference between (i) absorption of the second wavelength range by live human tissue, and (ii) absorption of the first wavelength range by live human tissue satisfies a threshold condition. The method further includes capturing a second image of the first subject under illumination of the second wavelength range, identifying, based on a difference between the first image and the second image, the first subject as an alternative representation of a live person, and preventing access to the secure system responsive to identifying the first subject as an alternative representation of a live person.

Spoof detection using dual-band near-infrared (NIR) imaging

The technology described in this document can be embodied in a method that includes 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 illuminating a subject with structured light using a light source array comprising multiple light sources disposed in a predetermined pattern, capturing an image of the subject as illuminated by the structured light, and determining that the image includes features representative of the predetermined pattern. The method also includes, responsive to determining that the image includes features representative of the predetermined pattern, identifying the subject in the image to be an alternative representation of a live person. The method further includes responsive to identifying the subject in the image to be an alternative representation of a live person, preventing access to the secure system.

Spoof detection using structured light illumination

The technology described in this document can be embodied in a method that includes receiving from a sensor, information indicative of an environmental condition. The method also includes receiving first information indicative of whether or not a first image captured by a first image acquisition device corresponds to an alternative representation of a live person, and receiving second information indicative of whether or not a second image captured by a second image acquisition device corresponds to the alternative representation. The first information and the second information are combined in a weighted combination, the corresponding weights being assigned in accordance with the environmental condition. A determination is made, based on the weighted combination, that a subject in the first and second images is an alternative representation of a live person, and in response, access to the secure system is prevented.

Spoof detection using multiple image acquisition devices

The technology described in this document can be embodied in a method for capturing an image. The method includes generating a first control signal configured to cause a rolling shutter camera to capture an image of a subject over a first time period. The method also includes generating, at a first time point during the first time period, a second control signal configured to set a multi-spectral illumination source at a first intensity level. The multi-spectral illumination source is configured to illuminate the subject. The method further includes generating, at a second time point during the first time period, a third control signal configured to set the multi-spectral illumination source at a second intensity level that is less than the first intensity level. A portion of the image captured by the rolling shutter camera between the first and second time points includes a target feature associated with the subject.

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Kansas City, MO, United States of America

Yash Joshi