PATENT CLAIM ANALYSIS

Application Number: 16268789
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-06
Patent Classification: ["382", "110000"]

Abstract:
A method for identifying the presence of fruit in image data in an image sensor of a scene includes acquiring image data in an image sensor for at least two distinct wavelengths of a scene. A normalized difference reflectivity index (NDRI) for each location in an array of locations in the image data is calculated with respect to said at least two distinct wavelengths. Regions in the array of locations are identified where the value of the calculated NDRI of the locations in these regions is within a range of values indicative of a presence of fruits in the scene. An output is generated on an output device with information related to the identified presence of fruits.

Claim (Index 15):
The computer program product according to  claim 12 , wherein said program code is executable to estimate a distribution of fruit sizes in the scene using a deep learning module.

Metadata:
- Claim Count in Document: 42.0
- Percentile: 99.0
- Lexical Diversity: 2.08475
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15353754', '15977771', '15868840', '14742074', '13907147']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2935550753067824
- 35 USC 102 Novelty (BERT): 0.5628068458186792
- Combined Prediction Score: 0.320480252357972
- Mean Citation Score: 219.810102
- Max Citation Score: 458.16928
- Similarity Product: 296.77615630393984

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