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US 11,113,553 B2Granted
Iris recognition using fully convolutional networks
AssigneeBrown University
InventorsSherief Reda, Hokchhay Tann, Heng Zhao
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Abstract
A method of accelerated iris recognition includes acquiring an image comprising at least an iris and a pupil, segmenting the iris and the pupil using a fully convolutional network (FCN) model, normalizing the segmented iris, encoding the normalized iris, the normalizing and encoding using a rubber sheet model and 1-D log Gabor filter, and masking the encoded iris.
Claims4
A method of accelerated iris recognition comprising:
- acquiring an image comprising at least an iris and a pupil;
- segmenting the iris and the pupil using a fully convolutional network (FCN) model and a circle fitting algorithm;
- normalizing the segmented iris;
- encoding the normalized iris, the normalizing and encoding using a rubber sheet model and 1-D log Gabor filter;
- and
- masking the encoded iris.
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A method of accelerated iris recognition comprising:
- exploring fully convolutional network (FCN) architectures for iris segmentation;
- evaluating a performance versus a complexity trade-off for each FCN architecture by executing a full end-to-end iris recognition pipeline;
- performing FCN selection based on its complexity and its end-to-end iris recognition performance such as equal error rate and receiver operating characteristics;
- evaluating FCN complexity by measuring parameter counts and execution latency on an accelerator running on an embedded field programmable gate array (FPGA) platform;
- and
- executing a full pipeline implementation on an embedded field programmable gate array (FPGA) platform.
3 more elements
Dependencies are inferred from the claim text.