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: Systems and methods are described for providing reliable biometric access control using an optical biometric sensor in a miniaturized form factor. Some implementations include multiple light sources that can illuminate skin or other tissue at multiple locations during a single measurement session. An imaging array can be arranged to form images of the light exiting the tissue only after undergoing diffuse reflectance in the tissue. Some implementations use the images to perform biometric functions. For example, the images can be used to identify an individual, verify identity of an individual, estimate demographic characteristics of an individual, etc. Such biometric functions can further be used to determine and affect access to secured assets.

Abstract: Systems and methods are described for providing reliable biometric access control using an optical biometric sensor in a miniaturized form factor. Some implementations include multiple light sources that can illuminate skin or other tissue at multiple locations during a single measurement session. An imaging array can be arranged to form images of the light exiting the tissue only after undergoing diffuse reflectance in the tissue. Some implementations use the images to perform biometric functions. For example, the images can be used to identify an individual, verify identity of an individual, estimate demographic characteristics of an individual, etc. Such biometric functions can further be used to determine and affect access to secured assets.

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.