Automated detection of carton damage
AssigneeTarget Brands, Inc.
InventorsMatthew Nokleby, Deepti Pachauri, Kenneth Zins
Life of this patent
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Abstract
Methods and systems for automated detection of carton defects are disclosed. One method includes capturing one or more images of a carton via a camera system at a routing location within a warehouse of a retail supply chain, and applying a machine learning model to determine a likelihood of damage of the carton. The method can include, based on the likelihood of damage being above a particular threshold, identifying the carton as damaged. A carton assessment record can be stored in a carton damage tracking database, including the one or more images of the carton alongside the likelihood of damage and the routing location.
Claims20
A method comprising:
- capturing an image of the conveyor system via a camera system at a routing location of a warehouse;
- applying a machine learning model to the image of the conveyor system;
- identifying a carton boundary of a carton in the image of the conveyor system;
- identifying a conveyor system segment boundary in the image of the conveyor system;
- determining, using the carton boundary and the conveyor system segment boundary, that the conveyor system segment includes the carton;
- identifying a second carton boundary of a second carton in the image of the conveyor system;
- and
- determining, using the second carton boundary and the conveyor system segment boundary, that the conveyor system segment includes the second carton.
A method comprising:
- capturing an image of a conveyor system via a camera system at a routing location of a warehouse;
- applying a machine learning model to the image of the conveyor system to identify a defect, wherein applying the machine learning model to the image of the conveyor system to identify the defect comprises determining that a conveyor system segment of the conveyor system includes a plurality of cartons;
- determining a likelihood that the conveyor system segment includes the plurality of cartons;
- and
- determining that the likelihood that the conveyor system segment includes the plurality of cartons is greater than a threshold.
A carton defect detection system comprising:
- an image capture system located at a routing location within a warehouse;
- an image analysis server local to the image capture system, the image analysis server communicatively connected to the image capture system and configured to host a database, the image analysis server configured to:
- receive an image of a conveyor system from the image capture system;
- apply a machine learning model to the image of the conveyor system, wherein applying the machine learning model includes:
- identifying a carton boundary of a carton in the image of the conveyor system;
- identifying the conveyor system segment boundary in the image of the conveyor system;
- determining, using the carton boundary and the conveyor system segment boundary that the conveyor system segment includes the carton;
- identifying a second carton boundary of a second carton in the image of the conveyor system;
- and
- determining, using the second carton boundary and the conveyor system segment boundary, that the conveyor system segment includes the second carton;
- and
- in response to determining that the conveyor system segment includes the first carton and the second carton, identifying a defect in handling the first carton and the second carton at the routing location.
Dependencies are inferred from the claim text.