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US 12,620,242 B2Granted
Systems and methods for printed circuit board netlist extraction from multimodal imagery
AssigneeBattelle Memorial Institute
InventorsAnthony F. George, John Timothy Balint, Thomas Kent
Life of this patent
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Abstract
A system and method for generating a netlist for a printed circuit board. In some embodiments, the method includes capturing image data of a circuit board from a plurality of sensors to generate a set of captured data for each of the plurality of sensors; extracting a plurality of features from the image data using machine learning; and generating a design associated with the circuit board from the plurality of features.
Claims18
A method comprising:
- capturing image data of a circuit board from a plurality of sensors to generate a set of captured data for each of the plurality of sensors;
- extracting a plurality of features from the image data using machine learning;
- wherein:
- the plurality of features include at least one of traces, pins, components, and/or text;
- the text is extracted using optical character recognition;
- the pins are extracted using a pin recognition neural network;
- the components are extracted using a component recognition neural network;
- and the traces are extracted using a Canny edge detector and a loss function, the loss function including a linear combination between an edge-based loss and a cross entropy loss, wherein the cross entropy loss operates as a pixel-based loss function;
- and generating a design associated with the circuit board from the plurality of features.
6 more elements
A system comprising:
- a plurality of sensors configured to capture image data of a circuit board to generate a set of captured data for each of the plurality of sensors;
- and a processor configured to:
- extract a plurality of features from the image data of the circuit board using machine learning;
- wherein:
- the plurality of features include at least one of traces, pins, components, and/or text;
- the text is extracted using optical character recognition;
- the pins are extracted using a pin recognition neural network;
- the components are extracted using a component recognition neural network;
- and the traces are extracted using a Canny edge detector and a loss function, the loss function including a linear combination between an edge-based loss and a cross entropy loss, wherein the cross entropy loss operates as a pixel-based loss function;
- and generate a design associated with the circuit board from the plurality of features.
7 more elements
A system comprising:
- a processor;
- a non-transitory computer-readable storage media;
- and program instructions stored on the non-transitory computer-readable storage media for execution by the processor, the stored program instructions including instructions to:
- capture image data of a circuit board from a plurality of sensors to generate a set of captured data for each of the plurality of sensors;
- extract a plurality of features from the image data using machine learning;
- wherein:
- the plurality of features include at least one of traces, pins, components, and/or text;
- the text is extracted using optical character recognition;
- the pins are extracted using a pin recognition neural network;
- the components are extracted using a component recognition neural network;
- and the traces are extracted using a Canny edge detector and a loss function, the loss function including a linear combination between an edge-based loss and a cross entropy loss, wherein the cross entropy loss operates as a pixel-based loss function;
- and generate a design associated with the circuit board from the plurality of features.
9 more elements
Dependencies are inferred from the claim text.