Reconfigurable fabric inspection system
AssigneeUniversity of North Texas
InventorsBugao XU, Wenbin OUYANG, Jinliang WEI
Life of this patent
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Abstract
A method of identifying defects in a fabric can include obtaining an image of a fabric on a loom, extracting feature points within the image to generate an input image, processing the input image with a machine learning model, detecting one or more defects within the input image using the machine learning model, and providing, by the machine learning model, an indication of a defect in the input image.
Claims33
A method of identifying defects in a fabric, the method comprising:
- obtaining an image of a fabric on a loom;
- extracting feature points within the image to generate an input image;
- processing the input image with a machine learning model;
- detecting one or more defects within the input image using the machine learning model;
- and
- providing, by the machine learning model, an indication of a defect in the input image.
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A method of identifying defects in a fabric, the method comprising:
- obtaining an image of a fabric on a loom;
- detecting one or more defects within the image using a first machine learning model;
- sending the image to a system controller in response to detecting the one or more defects within the image;
- verifying, by the system controller, a presence of the one or more defects within the image using a second machine learning model;
- and
- generating, by the system controller, an output signal in response to verifying the presence of the one or more defects within the image.
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A system for identifying defects in fabric, the system comprising:
- a contact image sensor (CIS) configured to be coupled to a loom and image a fabric on the loom;
- and
- a CIS controller in signal communication with the CIS, wherein the CIS controller comprises a processor, wherein the CIS controller is configured to:
- receive an image of the fabric on the loom;
- process the image with a machine learning model;
- identify one or more defects in the fabric using the machine learning model;
- and
- provide an output indicative of the presence of the one or more defects in the fabric.
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Dependencies are inferred from the claim text.