Abstract: An example method includes capturing, by a camera of a mobile computing device, an image, determining whether the image includes a representation of at least a portion of a face, and, when the image includes the representation of at least the portion of the face, analyzing characteristics of the image. The characteristics include at least one of a tonal distribution of the image that is associated with a darkness-based mapping of a plurality of pixels of the image, and a plurality of spatial frequencies of the image that are associated with a visual transition between adjacent pixels of the image. The method further includes classifying, by the mobile computing device, a quality of the image based at least in part on the analyzed characteristics of the image.

Abstract: An example method includes capturing, by an image capture device of a computing device, an image of a face of a user. The method further includes detecting, by the computing device, whether a distance between the computing device and an object represented by at least a portion of the image is less than a threshold distance, and, when the detected distance is less than a threshold distance, denying authentication to the user with respect to accessing one or more functionalities controlled by the computing device, where the authentication is denied independent of performing facial recognition based at least in part on the captured image.

Abstract: In general, this disclosure describes techniques for assessing image quality of captured facial images. An example method includes capturing an image, generating a facial detection confidence score based in part on a likelihood that a representation of at least a portion of a face is included in the image, generating a facial landmark detection confidence score based at least in part on a likelihood that representations of facial landmarks are accurately identified in the image, and generating a geometric consistency score based at least in part on a difference between a point of intersection between a nose base and a line segment that passes through each eye and a midpoint of the line segment. The method also includes generating an image quality score based in part on a combination of the confidence scores, and the consistency score, and classifying an image quality based on the image quality score.