Automated Glass Damage Assessment via Image Processing
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Solution Overview
Problem
The existing process for submitting and processing insurance claims for damaged motor vehicle glass is time-consuming and inefficient, requiring physical inspections by adjusters and lengthy procedures.
Innovation Solution
An automated system and method that uses image processing to assess damage, determine the type of glass, and detect fraud, allowing users to submit claims electronically by capturing and uploading images, which are then processed to determine repair or replacement needs, and flagging fraudulent claims.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical inspection by adjusters is used to process insurance claims, then accuracy of damage assessment is improved, but processing time and operational complexity increase
Solution Approach 1:
The patent replaces the mechanical system of physical adjuster inspection with an automated image processing system using machine learning algorithms. The system processes photographs of damaged glass to automatically determine damage type, severity, and repairability, eliminating the need for physical inspection while maintaining assessment accuracy.
Solution Approach 2:
The patent uses photographic copies of the damaged glass as substitutes for physical inspection. Multiple images from different angles and close-ups are captured and processed by the system to create a digital representation of the damage, allowing remote assessment without physical presence of adjusters.
2Reliability
If physical inspection by adjusters is used to process insurance claims, then fraud detection capability is improved, but device complexity and operational requirements increase
Solution Approach 1:
The patent implements feedback mechanisms where the image processing system continuously learns from verified claims and adjuster decisions. The system compares automated assessments with actual repair outcomes and uses this feedback to improve its fraud detection algorithms, enhancing reliability while maintaining automated operation.
Solution Approach 2:
The patent introduces an intermediary layer of automated image analysis between the claimant and the final approval process. This intermediary system pre-screens claims for potential fraud indicators before human review, reducing the complexity of manual fraud detection while improving overall system reliability.
3Productivity
If automated image processing is used to submit claims, then productivity and ease of operation are improved, but measurement precision and fraud detection accuracy may worsen
Solution Approach 1:
The patent performs preliminary actions by capturing multiple standardized images at specific angles and distances before processing. The system prepares the image set with required metadata and performs initial automated analysis to triage claims, enabling high-speed processing while maintaining accuracy through structured data collection.
Solution Approach 2:
The patent enables self-service claim submission where policyholders capture and upload their own images through a mobile interface. The system automatically processes these user-captured images through the same rigorous analysis pipeline, maintaining measurement precision while dramatically improving productivity and ease of operation.
4Measurement precision
If multiple images are required for claim submission, then measurement precision and fraud detection are improved, but loss of time and operational complexity increase
Solution Approach 1:
The patent implements dynamic image requirements that adapt based on the type of damage detected in initial images. The system adjusts the number and type of additional images needed in real-time, requesting only the minimum necessary images to achieve sufficient confidence in the assessment, thereby maintaining precision while improving ease of operation.
Solution Approach 2:
The patent changes the parameters of image capture requirements based on the specific claim context. The system modifies resolution requirements, angle specifications, and quantity of images needed based on the apparent severity and type of damage, optimizing the balance between measurement precision and operational simplicity for each individual claim.
Data Source
AI summary
Methods for submitting an insurance claim for damaged motor vehicle glass are provided that can include: receiving a plurality of images associated with motor vehicle glass at processing circuitry; performing image processing operations on each of the plurality of images to determine one or more of glass damage, glass type, and/or claim fraud; and submitting an insurance claim for motor vehicle glass repair or replace based on the glass type or damage, or flagging the claim as fraud.The present disclosure also provides a non-transitory computer readable storing instruction that when executed by a processor, causes a computer system to perform the following method. The method can include: prompting a user for initial claim submission information; prompting the user for a plurality of images of portions of motor vehicle glass; performing image processing operations on each of the plurality of images to train or improve the computer system, determine one or more of glass damage, glass type, and/or claim fraud; and one of submit or reject an insurance claim for glass repair.Glass vendors may be granted access to the systems and methods of the present disclosure and prompted to complete replacements as well.