Neural network for eye image segmentation and image quality estimation
First Claim
1. A system for eye image segmentation and image quality estimation, the system comprising:
- an eye-imaging camera configured to obtain an eye image;
non-transitory memory configured to store the eye image;
a hardware processor in communication with the non-transitory memory, the hardware processor programmed to;
receive the eye image;
process the eye image using a convolution neural network to generate a segmentation of the eye image; and
process the eye image using the convolution neural network to generate a quality estimation of the eye image,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 a first output layer of the shared layers is connected to a first input layer of the segmentation tower and to a second input layer of the segmentation tower, at least one of the first input layer or the second input layer comprising a concatenation layer,wherein the first output layer of the shared layers is connected to an input layer of the quality estimation layer, andwherein the eye image is received by an input layer of the shared layers.
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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.
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Citations
20 Claims
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1. A system for eye image segmentation and image quality estimation, the system comprising:
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an eye-imaging camera configured to obtain an eye image; non-transitory memory configured to store the eye image; a hardware processor in communication with the non-transitory memory, the hardware processor programmed to; receive the eye image; process the eye image using a convolution neural network to generate a segmentation of the eye image; and process the eye image using the convolution neural network to generate a quality estimation of the eye image, 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 a first output layer of the shared layers is connected to a first input layer of the segmentation tower and to a second input layer of the segmentation tower, at least one of the first input layer or the second input layer comprising a concatenation layer, wherein the first output layer of the shared layers is connected to an input layer of the quality estimation layer, and wherein the eye image is received by an input layer of the shared layers. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system for eye image segmentation and image quality estimation, the system comprising:
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an eye-imaging camera configured to obtain an eye image; non-transitory memory configured to store the eye image; a hardware processor in communication with the non-transitory memory, the hardware processor programmed to; receive the eye image; process the eye image using a convolution neural network to generate a segmentation of the eye image; and process the eye image using the convolution neural network to generate a quality estimation of the eye image, 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 the segmentation layers are not shared with the quality estimation tower, wherein the quality estimation layers are not shared with the segmentation tower, and wherein the eye image is received by an input layer of the shared layers. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification