Abstract: Disclosed herein are systems and methods for using machine learning for image-based spoof detection. One embodiment takes the form of a method that includes obtaining an input-data set that includes a plurality of images captured of a biometric-authentication subject by a plurality of cameras of a camera system. The method also includes inputting the input-data set into a trained machine-learning module, and processing the input-data set using the machine-learning module to obtain, from the machine-learning module, a spoof-detection result for the biometric-authentication subject. The method also includes outputting the spoof-detection result for the biometric-authentication subject.

Abstract: Disclosed herein are systems and methods for using machine learning for image-based spoof detection. One embodiment takes the form of a method that includes obtaining an input-data set that includes a plurality of images captured of a biometric-authentication subject by a plurality of cameras of a camera system. The method also includes inputting the input-data set into a trained machine-learning module, and processing the input-data set using the machine-learning module to obtain, from the machine-learning module, a spoof-detection result for the biometric-authentication subject. The method also includes outputting the spoof-detection result for the biometric-authentication subject.

Abstract: A method and device for protecting sensitive information stored on a mobile device capable of wireless communication is described. The protection is provided by permitting wireless transmission of the sensitive information only if data received from an optical sensor or a magnetic sensor satisfies a predetermined requirement.

Abstract: A method and device for protecting sensitive information stored on a mobile device capable of wireless communication is described. The protection is provided by permitting wireless transmission of the sensitive information only if data received from an optical sensor or a magnetic sensor satisfies a predetermined requirement.

Abstract: Methods and devices of studying a predefined portion of an object having a feature of interest are disclosed. The feature of interest defines a class of objects that includes the object. Light sources directly illuminate the object from different illumination directions. The light sources are maintained in a stable configuration relative to the object. For each illumination direction, an image is generated from light scattered from the object with a camera maintained in a stable configuration relative to the light sources. A methodology derived from machine learning for the class of objects is applied to filter the generated images are filtered for a characteristic consistent with the feature of interest. Surface gradients are determined from the filtered images and integrated to generate a topography of a surface of the object.

Abstract: Methods and sensors are disclosed for executing a biometric function. Illumination light is generated and directed to a deformable layer when the deformable layer is in a state of deformation resulting from pressure applied to the deformable layer by a skin site. Light scattered from the deformable layer is received. A fingerprint pattern of the skin site is determined from the received light. The biometric function is performed with the determined fingerprint pattern.

Abstract: Methods and devices of studying a predefined portion of an object having a feature of interest are disclosed. The feature of interest defines a class of objects that includes the object. Light sources directly illuminate the object from different illumination directions. The light sources are maintained in a stable configuration relative to the object. For each illumination direction, an image is generated from light scattered from the object with a camera maintained in a stable configuration relative to the light sources. A methodology derived from machine learning for the class of objects is applied to filter the generated images are filtered for a characteristic consistent with the fetaure of interest. Surface gradients are determined from the filtered images and integrated to generate a topography of a surface of the object.