US 11,776,131 B2 · Neural network for eye image segmentation and image quality estimation

Abstract

Systems and methods for eye image segmentation and image quality estimation are disclosed. In one aspect, after receiving an eye image, a device such as an augmented reality device can process the eye image using a convolutional neural network with a merged architecture to generate both a segmented eye image and a quality estimation of the eye image. The segmented eye image can include a background region, a sclera region, an iris region, or a pupil region. In another aspect, a convolutional neural network with a merged architecture can be trained for eye image segmentation and image quality estimation. In yet another aspect, the device can use the segmented eye image to determine eye contours such as a pupil contour and an iris contour. The device can use the eye contours to create a polar image of the iris region for computing an iris code or biometric authentication.

Claims20

Dependent claims

A method for training a convolutional neural network for eye image segmentation and image quality estimation, the method being performed by a system of one or more processors, and the method comprising:

obtaining a training set of eye images;
providing a convolutional neural network with the training set of eye images;
and training the convolutional neural network with the training set of eye images, wherein the convolution neural network comprises a segmentation tower and a quality estimation tower, wherein the segmentation tower comprises segmentation layers and shared layers,
wherein the quality estimation tower comprises quality estimation layers and the shared layers,
wherein an output layer of the shared layers is connected to a first input layer of the segmentation tower and a second input layer of the segmentation tower,
and wherein the output layer of the shared layers is connected to an input layer of the quality estimation layer.

3 more elements

A system comprising one or more processors and non-transitory computer storage media storing instructions that when executed by the one or more processors, cause the processors to perform operations comprising:

obtaining a training set of eye images;
providing a convolutional neural network with the training set of eye images;
and training the convolutional neural network with the training set of eye images, wherein the convolution neural network comprises a segmentation tower and a quality estimation tower, wherein the segmentation tower comprises segmentation layers and shared layers,
wherein the quality estimation tower comprises quality estimation layers and the shared layers,
wherein an output layer of the shared layers is connected to a first input layer of the segmentation tower and a second input layer of the segmentation tower,
and wherein the output layer of the shared layers is connected to an input layer of the quality estimation layer.

3 more elements

Dependencies are inferred from the claim text.

Neural network for eye image segmentation and image quality estimation

Life of this patent

Neural network for eye image segmentation and image quality estimation

Life of this patent

Abstract

Claims20