Abstract: In one embodiment, a method includes capturing, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum are attached to a fixture and the target is attached to the drum. The method also includes determining a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate is programmed into a drum encoder. The method further includes capturing, by the camera, a second image of the target while the target is rotated about an axis of the drum, determining a number of longitudinal pixels in a longitudinal pitch distance of the second image, and comparing the number of lateral pixels to the number of longitudinal pixels.

Abstract: In one embodiment, a method includes receiving, by a defect detector module, an image of a physical object and classifying, by the defect detector module, one or more first features from the image of the physical object into one or more first classifications using one or more machine learning algorithms. The method further includes analyzing, by the defect detector module, the one or more first classifications and determining, by the defect detector module, that the physical object comprises a defect based on analyzing the one or more first classifications.

Abstract: In one embodiment, a method includes receiving, by a defect detector module, an image of a physical object and classifying, by the defect detector module, one or more first features from the image of the physical object into one or more first classifications using one or more machine learning algorithms. The method further includes analyzing, by the defect detector module, the one or more first classifications and determining, by the defect detector module, that the physical object comprises a defect based on analyzing the one or more first classifications.

Abstract: In one embodiment, a method includes capturing, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum are attached to a fixture and the target is attached to the drum. The method also includes determining a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate is programmed into a drum encoder. The method further includes capturing, by the camera, a second image of the target while the target is rotated about an axis of the drum, determining a number of longitudinal pixels in a longitudinal pitch distance of the second image, and comparing the number of lateral pixels to the number of longitudinal pixels.

Abstract: In one embodiment, a method includes capturing, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum are attached to a fixture and the target is attached to the drum. The method also includes determining a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate is programmed into a drum encoder. The method further includes capturing, by the camera, a second image of the target while the target is rotated about an axis of the drum, determining a number of longitudinal pixels in a longitudinal pitch distance of the second image, and comparing the number of lateral pixels to the number of longitudinal pixels.

Abstract: In one embodiment, a method includes capturing, by a camera of an image capturing module, a first image of a target. The image capturing module and a drum are attached to a fixture and the target is attached to the drum. The method also includes determining a number of lateral pixels in a lateral pitch distance of the image of the target, determining a lateral object pixel size based on the number of lateral pixels, and determining a drum encoder rate based on the lateral object pixel size. The drum encoder rate is programmed into a drum encoder. The method further includes capturing, by the camera, a second image of the target while the target is rotated about an axis of the drum, determining a number of longitudinal pixels in a longitudinal pitch distance of the second image, and comparing the number of lateral pixels to the number of longitudinal pixels.

Abstract: In one embodiment, a method includes receiving, by a defect detector module, an image of a physical object and classifying, by the defect detector module, one or more first features from the image of the physical object into one or more first classifications using one or more machine learning algorithms. The method further includes analyzing, by the defect detector module, the one or more first classifications and determining, by the defect detector module, that the physical object comprises a defect based on analyzing the one or more first classifications.

Abstract: In one embodiment, a method includes receiving, by a defect detector module, an image of a physical object and classifying, by the defect detector module, one or more first features from the image of the physical object into one or more first classifications using one or more machine learning algorithms. The method further includes analyzing, by the defect detector module, the one or more first classifications and determining, by the defect detector module, that the physical object comprises a defect based on analyzing the one or more first classifications.

Abstract: In one embodiment, a method includes receiving, by a defect detector module, an image of a physical object and classifying, by the defect detector module, one or more first features from the image of the physical object into one or more first classifications using one or more machine learning algorithms. The method further includes analyzing, by the defect detector module, the one or more first classifications and determining, by the defect detector module, that the physical object comprises a defect based on analyzing the one or more first classifications.