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    Method on identifying indicia orientation and decoding indicia for machine vision systems
    2.
    发明授权
    Method on identifying indicia orientation and decoding indicia for machine vision systems 有权

    公开(公告)号：US11995900B2

    公开(公告)日：2024-05-28

    申请号：US17524983

    申请日：2021-11-12

    Applicant: ZEBRA TECHNOLOGIES CORPORATION

    Inventor： Yan Zhang ,  Denghui Xiao

    IPC: G06V20/62 ,  G06F18/2413 ,  G06N3/02 ,  G06T7/60 ,  G06T7/70

    CPC classification number: G06V20/63 ,  G06F18/24137 ,  G06N3/02 ,  G06T7/60 ,  G06T7/70

    Abstract: A method and system for performing indicia recognition includes obtaining, at an image sensor, an image of an object of interest and identifying at least one region of interest in the image. The region of interest contains one or more indicia indicative of the object of interest. The processor then determines positions of each region of interest and further determines a geometric shape based on the positions of each of the regions of interest. An orientation classification is identified for each region of interest is based on a respective position relative to the geometric shape for reach region of interest. The processor then identifies and performs one or more transformations for each region of interest, with each transformation determined by each regions respective orientation classification. The processor then performs indicia recognition on each of the one or more transformed regions of interest.

    METHOD ON IDENTIFYING INDICIA ORIENTATION AND DECODING INDICIA FOR MACHINE VISION SYSTEMS
    4.
    发明公开
    METHOD ON IDENTIFYING INDICIA ORIENTATION AND DECODING INDICIA FOR MACHINE VISION SYSTEMS 审中-公开

    公开(公告)号：US20230154212A1

    公开(公告)日：2023-05-18

    申请号：US17524983

    申请日：2021-11-12

    Applicant: ZEBRA TECHNOLOGIES CORPORATION

    Inventor： Yan Zhang ,  Denghui Xiao

    IPC: G06K9/32 ,  G06K9/62 ,  G06T7/70 ,  G06T7/60 ,  G06N3/02

    CPC classification number: G06K9/3258 ,  G06K9/6272 ,  G06T7/70 ,  G06T7/60 ,  G06N3/02

    Abstract: A method and system for performing indicia recognition includes obtaining, at an image sensor, an image of an object of interest and identifying at least one region of interest in the image. The region of interest contains one or more indicia indicative of the object of interest. The processor then determines positions of each region of interest and further determines a geometric shape based on the positions of each of the regions of interest. An orientation classification is identified for each region of interest is based on a respective position relative to the geometric shape for reach region of interest. The processor then identifies and performs one or more transformations for each region of interest, with each transformation determined by each regions respective orientation classification. The processor then performs indicia recognition on each of the one or more transformed regions of interest.

    IMAGE-BASED ANOMALY DETECTION BASED ON A MACHINE LEARNING ANALYSIS OF AN OBJECT
    5.
    发明申请
    IMAGE-BASED ANOMALY DETECTION BASED ON A MACHINE LEARNING ANALYSIS OF AN OBJECT 有权

    公开(公告)号：US20220383128A1

    公开(公告)日：2022-12-01

    申请号：US17334162

    申请日：2021-05-28

    Applicant: ZEBRA TECHNOLOGIES CORPORATION

    Inventor： Daniel S. Gonzales ,  Yan Zhang ,  Andrea Mirabile ,  Alessandro Bay

    IPC: G06N3/08 ,  G06N20/10 ,  G06N5/04 ,  G06N3/04

    Abstract: An object analysis system is disclosed herein. The object analysis system may receive an input image that depicts an object. The object analysis system may determine, using a feature extraction model and from the input image, a first feature output that is associated with one or more features of the object. The feature extraction model may be trained based on reference images that depict reference objects that are a type of the object. The object analysis system may determine, using a classification model, that an anomaly status of the object is indicative of the object including an anomaly. The classification model may be trained based on the reference images. The object analysis system may determine, using an anomaly localization model, a location of the anomaly in the input image based on a second feature output of the convolutional neural network encoder. The anomaly localization model may be trained based on the reference images. The object analysis system may perform an action associated with the location of the anomaly.

    Automated chute fullness detection
    6.
    发明授权
    Automated chute fullness detection 有权

    公开(公告)号：US11210549B2

    公开(公告)日：2021-12-28

    申请号：US16824038

    申请日：2020-03-19

    Applicant: ZEBRA TECHNOLOGIES CORPORATION

    Inventor： Bin Sun ,  Yan Zhang ,  Kevin J. O'Connell ,  Yun Fu

    IPC: G06K9/46 ,  G06K9/32 ,  G06N3/08 ,  B65G11/20 ,  G06T7/00

    Abstract: A method includes: storing (i) a reference image of a chute for receiving objects, and (ii) a region of interest mask corresponding to a location of the chute in a field of view of an image sensor; at a processor, controlling the image sensor to capture an image of the chute; applying an illumination adjustment to the image; selecting, at the processor, a portion of the image according to the region of interest mask; generating a detection image based on a comparison of the selected portion and the reference image; determining, based on the detection image, a fullness indicator for the chute; and providing the fullness indicator to notification system.

    THREE-DIMENSIONAL (3D) DEPTH IMAGING SYSTEMS AND METHODS FOR DYNAMIC CONTAINER AUTO-CONFIGURATION
    7.
    发明申请
    THREE-DIMENSIONAL (3D) DEPTH IMAGING SYSTEMS AND METHODS FOR DYNAMIC CONTAINER AUTO-CONFIGURATION 有权

    公开(公告)号：US20210012522A1

    公开(公告)日：2021-01-14

    申请号：US16509228

    申请日：2019-07-11

    Applicant: ZEBRA TECHNOLOGIES CORPORATION

    Inventor： Lichen Wang ,  Yan Zhang ,  Kevin J. O'Connell

    IPC: G06T7/70 ,  H04N13/207 ,  G06T7/13 ,  H04N5/225 ,  G06T7/521

    Abstract: Three-dimensional (3D) depth imaging systems and methods are disclosed for dynamic container auto-configuration. A 3D-depth camera captures 3D image data of a shipping container located in a predefined search space during a shipping container loading session. An auto-configuration application determines a representative container point cloud and (a) loads an initial pre-configuration file that defines a digital bounding box having dimensions representative of the predefined search space and an initial front board area; (b) applies the digital bounding box to the container point cloud to remove front board interference data from the container point cloud based on the initial front board area; (c) generates a refined front board area based on the shipping container type; (d) generates an adjusted digital bounding box based on the refined front board area; and (e) generates an auto-configuration result comprising the adjusted digital bounding box containing at least a portion of the container point cloud.

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