公开(公告)号：US20110150334A1

公开(公告)日：2011-06-23

申请号：US13055250

申请日：2009-07-22

Applicant: Eliza Yingzi Du ,  Zhi Zhou ,  Emrah Arslanturk

Inventor： Eliza Yingzi Du ,  Zhi Zhou ,  Emrah Arslanturk

IPC: G06K9/34

CPC classification number: G06K9/00604

Abstract: A method segments iris images from eye image data captured from non-cooperative subjects. The method includes receiving a frame of eye image data, and determining whether a pupil exists in the image by detecting glare areas in the image. Upon finding a pupil, subsequent images are processed with reference to the pupil location and a radius is calculated for the pupil. A k means clustering method and principal component analysis are used to locate pupil boundary points, which are fitted to a conic. Using the pupil boundary, an angular derivative is computed for each frame having a pupil and iris boundary points are fitted to a conic to identify an iris region between the iris boundary and the pupil boundary. Noise data are then removed from the iris region to generate an iris segment. A method for evaluating iris frame quality and iris image segmentation quality is also disclosed.

Abstract translation: 一种方法从非合作对象捕获的眼图数据中分割虹膜图像。 该方法包括接收一帧眼图数据，并通过检测图像中的眩光区域来确定图像中是否存在瞳孔。 在找到瞳孔时，参考瞳孔位置处理随后的图像，并计算瞳孔的半径。 A k表示聚类方法，主成分分析用于定位适合于锥体的瞳孔边界点。 使用瞳孔边界，对于具有瞳孔的每个帧计算角度导数，并且将虹膜边界点拟合到圆锥，以识别虹膜边界和瞳孔边界之间的虹膜区域。 然后从虹膜区域移除噪声数据，以产生虹膜段。 还公开了一种用于评估虹膜框架质量和虹膜图像分割质量的方法。

公开(公告)号：US08644565B2

公开(公告)日：2014-02-04

申请号：US13055250

申请日：2009-07-22

Applicant: Eliza Yingzi Du ,  Zhi Zhou ,  Emrah Arslanturk

Inventor： Eliza Yingzi Du ,  Zhi Zhou ,  Emrah Arslanturk

IPC: G06K9/00

CPC classification number: G06K9/00604

Abstract: A method segments iris images from eye image data captured from non-cooperative subjects. The method includes receiving a frame of eye image data, and determining whether a pupil exists in the image by detecting glare areas in the image. Upon finding a pupil, subsequent images are processed with reference to the pupil location and a radius is calculated for the pupil. A k means clustering method and principal component analysis are used to locate pupil boundary points, which are fitted to a conic. Using the pupil boundary, an angular derivative is computed for each frame having a pupil and iris boundary points are fitted to a conic to identify an iris region between the iris boundary and the pupil boundary. Noise data are then removed from the iris region to generate an iris segment. A method for evaluating iris frame quality and iris image segmentation quality is also disclosed.

Abstract translation: 一种方法从非合作对象捕获的眼图数据中分割虹膜图像。 该方法包括接收一帧眼图数据，并通过检测图像中的眩光区域来确定图像中是否存在瞳孔。 在找到瞳孔时，参考瞳孔位置处理随后的图像，并计算瞳孔的半径。 A k表示聚类方法，主成分分析用于定位适合于锥体的瞳孔边界点。 使用瞳孔边界，对于具有瞳孔的每个帧计算角度导数，并且将虹膜边界点拟合到圆锥，以识别虹膜边界和瞳孔边界之间的虹膜区域。 然后从虹膜区域移除噪声数据，以产生虹膜段。 还公开了一种用于评估虹膜框架质量和虹膜图像分割质量的方法。

公开(公告)号：US08577095B2

公开(公告)日：2013-11-05

申请号：US13257523

申请日：2010-03-19

Applicant: Eliza Yingzi Du ,  Craig Belcher

Inventor： Eliza Yingzi Du ,  Craig Belcher

IPC: G06K9/00

CPC classification number: G06K9/0061

Abstract: A method processes segmented iris images obtained by a non-cooperative image acquisition system to generate descriptors for features in the segmented iris image that are tolerant of segmentation error. The method includes receiving a segmented iris image, and selecting feature points in the segmented iris image to describe an iris locally.

Abstract translation: 一种方法处理由非合作图像采集系统获得的分割的虹膜图像，以生成分割虹膜图像中容许分割误差的特征的描述符。 该方法包括接收分割的虹膜图像，并且选择分割的虹膜图像中的特征点以局部地描述虹膜。

公开(公告)号：US20190073798A1

公开(公告)日：2019-03-07

申请号：US16153755

申请日：2018-10-06

Applicant: Eliza Yingzi Du

Inventor： Eliza Yingzi Du

IPC: G06T7/00 ,  G06T7/73 ,  G06T19/00 ,  H04L29/08 ,  G06F15/18

Abstract: Disclosed herein are methods and systems for real-time holographic augmented reality image processing. The processing includes the steps of receiving, at a cluster of servers and from an image capturing component, real-time image data; extracting one or more objects or a scene from the real-time image data based on results from real-time adaptive learning and one or more object/scene extraction parameters; extracting one or more human objects from the real-time image data based on results from real-time adaptive human learning and one or more human extraction parameters, receiving augmented reality (AR) input data; and creating holographic AR image data by projecting, for each image, the extracted object or scene, the extracted human object, and the AR input data using a multi-layered mechanism based on projection parameters. The real-time adaptive learning comprises object learning, object recognition, object segmentation, scene learning, scene recognition, scene segmentation, or a combination thereof. The real-time adaptive human learning comprises human characteristic learning, human recognition, human segmentation, human body movement tracking, or a combination thereof.

公开(公告)号：US20120140992A1

公开(公告)日：2012-06-07

申请号：US13257523

申请日：2010-03-19

Applicant: Eliza Yingzi Du ,  Craig Belcher

Inventor： Eliza Yingzi Du ,  Craig Belcher

IPC: G06K9/34 ,  G06K9/46

CPC classification number: G06K9/0061

Abstract: A method processes segmented iris images obtained by a non-cooperative image acquisition system to generate descriptors for features in the segmented iris image that are tolerant of segmentation error. The method includes receiving a segmented iris image, and selecting feature points in the segmented iris image to describe an iris locally.

Abstract translation: 一种方法处理由非合作图像采集系统获得的分割的虹膜图像，以生成分割虹膜图像中容许分割误差的特征的描述符。 该方法包括接收分割的虹膜图像，并且选择分割的虹膜图像中的特征点以局部地描述虹膜。

公开(公告)号：US10796456B2

公开(公告)日：2020-10-06

申请号：US16153755

申请日：2018-10-06

Applicant: Eliza Yingzi Du

Inventor： Eliza Yingzi Du

IPC: G06T7/00 ,  G06T7/73 ,  G06T19/00 ,  G06K9/00 ,  G06K9/03 ,  G06N3/08 ,  H04L29/08 ,  G06N20/00 ,  G06T11/00 ,  G06N7/00 ,  G06N5/00

Abstract: Disclosed herein are methods and systems for real-time holographic augmented reality image processing. The processing includes the steps of receiving, at a cluster of servers and from an image capturing component, real-time image data; extracting one or more objects or a scene from the real-time image data based on results from real-time adaptive learning and one or more object/scene extraction parameters; extracting one or more human objects from the real-time image data based on results from real-time adaptive human learning and one or more human extraction parameters, receiving augmented reality (AR) input data; and creating holographic AR image data by projecting, for each image, the extracted object or scene, the extracted human object, and the AR input data using a multi-layered mechanism based on projection parameters. The real-time adaptive learning comprises object learning, object recognition, object segmentation, scene learning, scene recognition, scene segmentation, or a combination thereof. The real-time adaptive human learning comprises human characteristic learning, human recognition, human segmentation, human body movement tracking, or a combination thereof.

公开(公告)号：US08818048B2

公开(公告)日：2014-08-26

申请号：US13010886

申请日：2011-01-21

Applicant: Eliza Yingzi Du ,  Kai Yang

Inventor： Eliza Yingzi Du ,  Kai Yang

IPC: G06K9/00

CPC classification number: G06K9/0061

Abstract: A method of generating a biometric feature descriptor has been developed that includes acquiring an image of an anatomical feature having a biometric feature, isolating a region of the image having the biometric feature, extracting image data from the image of the region to identify a plurality of features for the biometric feature, transforming the extracted image data for each identified feature into a plurality of feature descriptors, mapping the feature descriptors for the plurality of features into a first arrangement of feature descriptors, generating a second arrangement of feature descriptors with a non-invertible transform of the first arrangement of feature descriptors, and storing the second arrangement of feature descriptors into an electronic database.

Abstract translation: 已经开发了生成生物特征描述符的方法，其包括获取具有生物特征的解剖特征的图像，隔离具有生物特征的图像的区域，从该区域的图像中提取图像数据以识别多个 用于生物特征的特征，将针对每个识别的特征的提取的图像数据变换成多个特征描述符，将多个特征的特征描述符映射到特征描述符的第一布置中，生成具有非特征描述符的特征描述符的第二布置， 特征描述符的第一布置的可逆变换，以及将特征描述符的第二布置存储到电子数据库中。

公开(公告)号：US08768014B2

公开(公告)日：2014-07-01

申请号：US13144517

申请日：2010-01-14

Applicant: Eliza Yingzi Du ,  Darrell WuDunn ,  N. Luke Thomas

Inventor： Eliza Yingzi Du ,  Darrell WuDunn ,  N. Luke Thomas

IPC: G06K9/00

CPC classification number: G06K9/0061 ,  G06K2009/00932

Abstract: A method for obtaining an identification characteristic for a subject includes acquiring an image of an eye of the subject, segmenting the eye image into different regions, extracting features in a sclera region segmented from the eye image, and generating data identifying at least one feature extracted from the sclera region of the eye image.

Abstract translation: 一种用于获得对象的识别特征的方法包括获取对象的眼睛的图像，将眼睛图像分割成不同的区域，从眼睛图像分割的巩膜区域中提取特征，以及生成标识提取的至少一个特征的数据 从巩膜区域的眼睛图像。

公开(公告)号：US20120163678A1

公开(公告)日：2012-06-28

申请号：US13144517

申请日：2010-01-14

Applicant: Eliza Yingzi Du ,  Darrell WuDunn ,  N. Luke Thomas

Inventor： Eliza Yingzi Du ,  Darrell WuDunn ,  N. Luke Thomas

IPC: G06K9/62

CPC classification number: G06K9/0061 ,  G06K2009/00932

Abstract: A method for obtaining an identification characteristic for a subject includes acquiring an image of an eye of the subject, segmenting the eye image into different regions, extracting features in a sclera region segmented from the eye image, and generating data identifying at least one feature extracted from the sclera region of the eye image.

Abstract translation: 一种用于获得对象的识别特征的方法包括获取对象的眼睛的图像，将眼睛图像分割成不同的区域，从眼睛图像分割的巩膜区域中提取特征，以及生成标识提取的至少一个特征的数据 从巩膜区域的眼睛图像。

公开(公告)号：US20120249297A1

公开(公告)日：2012-10-04

申请号：US13396551

申请日：2012-02-14

Applicant: Eliza Yingzi Du ,  Kai Yang

Inventor： Eliza Yingzi Du ,  Kai Yang

IPC: G06F7/04

CPC classification number: G07C9/00158

Abstract: A system with its methods of detecting whether users are willing to access the biometric systems has been developed that includes acquiring the signal of an anatomical feature having a biometric feature, acquiring a dynamic feature for willingness test with/without biometric feature, isolating a region of the signal having the biometric feature, extracting feature descriptors from the region to identify a user, extracting a unique user consent signature from the dynamic feature for willingness test, storing the of feature descriptors and willingness signature into an electronic database and matching the feature descriptors and consent signatures with the ones stored in the electronic database during registration. Two types of consent biometrics schemes with two authentication example designs are developed.

Abstract translation: 已经开发了一种具有检测用户是否愿意访问生物测定系统的方法的系统，其包括获取具有生物特征的解剖特征的信号，获取具有/不具有生物特征的意愿测试的动态特征， 具有生物特征的信号，从该区域提取特征描述符以识别用户，从用于意愿测试的动态特征中提取唯一的用户同意签名，将特征描述符和意愿签名存储到电子数据库中并匹配特征描述符和 注册期间与电子数据库中存储的同意签名。 开发了具有两个认证示例设计的两种类型的同意生物识别方案。