Patents by Inventor Kevin Bowyer

Kevin Bowyer has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11768926
    Abstract: Systems and methods for detecting textured contact lenses in an iris image are disclosed. Initially, “K” images are taken of an eye in near-infrared light, each for a different positioning of the illuminant. Three-dimensional properties of the hypothetical iris are estimated based on image processing methods. The variability of the estimated three-dimensional properties is calculated, and a classification into two classes is made based on the variability. A low variability denotes that an authentic iris pattern was presented to the sensor, whereas a high variability denotes that the sensor observes an eye wearing a textured contact lens. The systems and methods disclosed allow for detecting presentation attacks to iris recognition systems/sensors based on presentation of an eye wearing a textured contact lens in an automatic and accurate way.
    Type: Grant
    Filed: October 24, 2019
    Date of Patent: September 26, 2023
    Assignee: University of Notre Dame Du Lac
    Inventors: Adam Czajka, Kevin Bowyer, Zhaoyuan Fang
  • Publication number: 20220240865
    Abstract: The video based detection of pulse waveform includes systems, devices, methods, and computer-readable instructions for capturing a video stream including a sequence of frames, processing each frame of the video stream to spatially locate a region of interest, cropping each frame of the video stream to encapsulate the region of interest, processing the sequence of frames, by a 3-dimensional convolutional neural network, to determine the spatial and temporal dimensions of each frame of the sequence of frames and to produce a pulse waveform point for each frame of the sequence of frames, and generating a time series of pulse waveform points to generate the pulse waveform of the subject for the sequence of frames.
    Type: Application
    Filed: February 3, 2022
    Publication date: August 4, 2022
    Inventors: Jeremy Speth, Patrick Flynn, Adam Czajka, Kevin Bowyer, Nathan Carpenter, Leandro Olie
  • Publication number: 20210319239
    Abstract: Systems and methods for detecting textured contact lenses in an iris image are disclosed. Initially, “K” images are taken of an eye in near-infrared light, each for a different positioning of the illuminant. Three-dimensional properties of the hypothetical iris are estimated based on image processing methods. The variability of the estimated three-dimensional properties is calculated, and a classification into two classes is made based on the variability. A low variability denotes that an authentic iris pattern was presented to the sensor, whereas a high variability denotes that the sensor observes an eye wearing a textured contact lens. The systems and methods disclosed allow for detecting presentation attacks to iris recognition systems/sensors based on presentation of an eye wearing a textured contact lens in an automatic and accurate way.
    Type: Application
    Filed: October 24, 2019
    Publication date: October 14, 2021
    Inventors: Adam Czajka, Kevin Bowyer, Zhaoyuan Fang
  • Publication number: 20100202669
    Abstract: Embodiments of the present invention include but are not limited to methods and systems for iris recognition. An iris recognition method may comprise comparing a plurality of images of an iris to determine at least one of one or more consistent features and one or more inconsistent features of the iris; and constructing an enrollment template for the iris based at least in part on the at least one of the one or more consistent features and the one or more inconsistent features.
    Type: Application
    Filed: September 24, 2007
    Publication date: August 12, 2010
    Applicant: UNIVERSITY OF NOTRE DAME DU LAC
    Inventors: Karen Hollingsworth, Kevin Bowyer, Patrick Flynn