PATENT CLAIM ANALYSIS

Application Number: 16097502
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-05
Patent Classification: ["358", "406000"]

Abstract:
A method for calibrating a multi-function printing (MFP) device includes printing a calibration target image on a first side of a print medium from at least one print medium source with a printing device of the MFP device. The calibration target image includes at least one fiducial. The method includes scanning the first side of the print medium comprising the calibration target image with a scanning device of the MFP device to create a first scanned image, identifying at least one edge of the print medium via a background pattern to determine a number of scan measurements, identifying at least one position of the at least one fiducial within the calibration target image, and calculating a calibration target error based on the at least one fiducial and the scan measurements.

Claim (Index 10):
A multifunction printing (MFP) device comprising:\n a scanning device; a background of the scanning device comprising a repeating series of alternating darker tones and lighter tones perpendicular to a scan direction of the scanning device; a memory device comprising a calibration target image stored thereon; a printing device to print the calibration target image on a plurality of print media from a corresponding number of print medium sources; and a calibration engine to, for each of the plurality of print media, calculate a calibration target error based on a number of fiducials within the calibration target image and a number of scan measurements defined by the background.

Metadata:
- Claim Count in Document: 35.0
- Percentile: 97.0
- Lexical Diversity: 2.65385
- Patent Class: 358.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['13327865', '10273286', '12868311', '09792853', '15427493']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4364375574443307
- 35 USC 102 Novelty (BERT): 0.4735861200981404
- Combined Prediction Score: 0.4401524137097117
- Mean Citation Score: 150.895236
- Max Citation Score: 168.16678000000005
- Similarity Product: 133.9001499597621

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test