Mobile Image Processing for Vehicle Damage Assessment
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Solution Overview
Problem
Conventional auto insurance claim settlement processes are lengthy due to the need for manual surveys and assessments, requiring significant labor and professional knowledge, and existing solutions for guiding users to take vehicle damage photos are inefficient, often requiring precise requirements and remote guidance.
Innovation Solution
An image processing method and apparatus using a mobile device with a camera, employing convolutional neural networks for image classification and target detection, to acquire, classify, and segment vehicle damage images, providing real-time prompts to users for improving image quality and relevance, and associating photos for accurate damage assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual survey and damage assessment personnel are deployed to conduct on-site survey and damage assessment, then the accuracy of damage assessment is improved, but the claim settlement cycle is extended and labor costs increase
Solution Approach 1:
The system enables users to independently complete damage photo acquisition without requiring manual surveyors. The mobile device automatically guides users through the photo-taking process using on-screen instructions and real-time image quality feedback, allowing users to self-service the damage documentation process while maintaining assessment accuracy.
Solution Approach 2:
The patent replaces the mechanical system of manual surveyor deployment with an automated electronic system. The mobile device with integrated camera, display, and processing algorithms substitutes human surveyors for the photo acquisition phase, eliminating travel time and manual coordination while preserving damage assessment capabilities through automated image analysis.
2Manufacturing precision
If users are required to take vehicle damage photos according to specific requirements (sharpness, brightness, shooting angle), then the quality of assessment photos is improved, but the complexity of guidance and operation increases
Solution Approach 1:
The system provides real-time feedback to users during the photo-taking process. The display shows captured images with overlaid guidance information indicating whether the photo meets quality requirements for sharpness, brightness, and shooting angle. This immediate feedback loop allows users to adjust their photos on the spot without requiring complex pre-instructions or multiple retakes.
Solution Approach 2:
The system performs preliminary analysis of captured images before final submission. The processing unit evaluates image quality parameters (sharpness, brightness, angle) in real-time and provides guidance before the user commits to using the photo. This preliminary action prevents poor-quality photos from proceeding further in the workflow, eliminating the need for complex post-acquisition filtering.
Data Source
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AI summary
An image processing method and apparatus are disclosed in embodiments of this specification. The method is performed at a mobile device that comprises a camera. The method comprises: acquiring a video stream of an accident vehicle by the camera according to a user instruction; obtaining an image of a current frame in the video stream; determining whether the image meets a predetermined criterion by inputting the image into a predetermined classification model; adding a target box and/or target segmentation information to the image by inputting the image into a target detection and segmentation model when the image meets the predetermined criterion, wherein the target box and the target segmentation information both correspond to at least one of vehicle parts and vehicle damage of the vehicle; and displaying the target box and/or the target segmentation information to the user.