Manufacturing Part Identification Using Computer Vision And Machine Learning

A manufacturing part identification system comprising:

• an augmented reality device comprising a camera;
• a server in communication with the augmented reality device comprising computer readable storage media storing instructions that, when executed by one or more processors cause the one or more processors to:
• receive an image comprising a manufacturing part from the augmented reality device;
• determine a contour outline of the manufacturing part based on the image;
• and
• determine a bounding perimeter encapsulating the manufacturing part;
• and
• a neural network in communication with the server, wherein the neural network is configured to:
• determine a prediction label for the manufacturing part;
• and
• determine a confidence value comprising a statistical likelihood that the prediction label is correct.

Computer readable storage media storing instructions that, when executed by one or more processors, cause the one or more processors to:

• receive an image comprising a manufacturing part from an augmented reality device;
• apply a color and magnitude of gradients threshold to the image such that a background of the image is mostly eliminated, and a contour of the manufacturing part remains;
• determine a contour outline of the manufacturing part;
• determine a bounding perimeter encapsulating the contour outline;
• receive a prediction label and a confidence value for the manufacturing part from a convolutional deep neural network;
• generate a message comprising the image, the prediction label, and the confidence value;
• and
• provide the message to the augmented reality device.