DEFECT CLASSIFICATION IN AN IMAGE OR PRINTED OUTPUT
First Claim
Patent Images
1. A monitoring device, comprising:
- circuitry to compare a printed output with a reference representing a target output and to determine potential defects in the printed output based on the comparison; and
circuitry to implement a convolutional neural network to classify each potential defect as a true defect or a false alarm.
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Abstract
A monitoring device includes circuitry to compare a printed output with a reference representing a target output and to determine potential defects in the printed output based on the comparison. The monitoring device further includes and circuitry to implement a convolutional neural network to classify each potential defect as a true defect or a false alarm.
10 Citations
15 Claims
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1. A monitoring device, comprising:
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circuitry to compare a printed output with a reference representing a target output and to determine potential defects in the printed output based on the comparison; and circuitry to implement a convolutional neural network to classify each potential defect as a true defect or a false alarm. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method comprising:
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receiving a first image and a second image, the first image and the second image being digital images; comparing the first image with the second image to detect differences between the first image and the second image; classifying differences detected by the comparing as a true defect or a false alarm using a neural network; and outputting the result of the classification. - View Dependent Claims (11)
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12. Machine-readable instructions provided on at least one machine-readable medium, the instructions to cause processing circuitry to:
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compare a printed image with a reference image and determine potential defects in the printed image based on the comparison; and implement a neural network to classify each potential defect as a true defect or a false alarm. - View Dependent Claims (13, 14, 15)
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Specification