PATENT CLAIM ANALYSIS

Application Number: 16153499
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-05
Patent Classification: ["382", "104000"]

Abstract:
Various embodiments disclosed herein are directed to methods of capturing Vehicle Identification Numbers (VIN) from images captured by a mobile device. Capturing VIN data can be useful in several applications, for example, insurance data capture applications. There are at least two types of images supported by this technology: (1) images of documents and (2) images of non-documents.

Claim (Index 8):
A system for identifying a field in an image of a non-document, comprising:\n a mobile device, the mobile device comprising:\n a memory configured to store the image, and \n a processor coupled with the memory, the processor configured to capture an image which includes a vehicle identification number (VIN) and cause the mobile device to transmit the captured image to a server; and \n a server configured to:\n receive the captured image, \n make a color assumption with respect to the VIN, \n identify candidate text strings that may include the VIN, \n perform an optical character recognition (OCR) on the candidate text strings, \n send the candidate text strings for validation, and \n in response to a candidate test string being validated, receive a confirmed VIN value for the validated candidate text strings.

Metadata:
- Claim Count in Document: 36.0
- Percentile: 97.0
- Lexical Diversity: 1.35294
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15714362', '14217361', '13844303', '13799513', '13844476']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2951967610921675
- 35 USC 102 Novelty (BERT): 0.5628682717172957
- Combined Prediction Score: 0.3219639121546803
- Mean Citation Score: 255.66338800000003
- Max Citation Score: 429.67615
- Similarity Product: 375.1303396386802

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