PATENT CLAIM ANALYSIS

Application Number: 16176921
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-02
Patent Classification: ["358", "003260"]

Abstract:
An image reading apparatus according to an embodiment includes an image reading unit configured to generate reference data by reading a reference surface and to generate image data by reading a sheet. A reference unit has a reference surface. A shading correction unit determines whether a portion of the reference surface includes a contaminant based on image data generated by the image reading unit reading the portion of the reference unit. When the portion of the reference surface is determined to not include a contaminant, the shading correction unit generates reference data based on the image data generated by the image reading unit reading the portion of the reference surface determined to not include a contaminant.

Claim (Index 6):
The image reading apparatus according to  claim 1 , wherein\n the controller is configured to\n execute a contaminant detection process with respect to the reference surface within an imaging range of the scanner by comparing the reference value with each of brightness values of the reference surface, and \n when the contaminant is detected in the contaminant detection process, rotate the reference roller by a predetermined amount angle and repeat the contaminant detection process until a total number of the rotation reaches a predetermined number.

Metadata:
- Claim Count in Document: 15.0
- Percentile: 97.0
- Lexical Diversity: 3.025
- Patent Class: 358.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15404765', '16028078', '15401532', '13105531', '12926212']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5165366643000525
- 35 USC 102 Novelty (BERT): 0.4969444136280493
- Combined Prediction Score: 0.5145774392328522
- Mean Citation Score: 177.96453200000005
- Max Citation Score: 239.13354
- Similarity Product: 181.6244528796923

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

Dataset: test