Multi-Camera Damage Detection Portal for Consistent Vehicle Inspection
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Solution Overview
Problem
Conventional vehicle inspection for damage is a manual, time-intensive process prone to variability and financial losses due to human expertise differences, leading to inconsistent results.
Innovation Solution
A system that captures multi-view image data from multiple cameras positioned in three-dimensional space, uses correspondence information to link images, and applies neural networks for automated damage detection, presenting results via a graphical user interface with heat maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual inspection is used, then flexibility and adaptability are maintained, but inspection time increases and consistency decreases
Solution Approach 1:
The patent replaces the manual mechanical inspection process with an automated optical system using multiple cameras and image processing algorithms. The system captures images from multiple angles and uses correspondence information to automatically identify damage, eliminating human variability and significantly increasing inspection speed while maintaining consistent results.
Solution Approach 2:
The system creates a digital copy of the object through multi-view imaging and correspondence mapping. By generating a virtual representation with linked locations from different camera perspectives, the system enables automated damage detection without physical contact, improving both speed and consistency compared to manual inspection.
2Measurement precision
If multiple cameras are used to capture images from different locations, then damage detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent makes the camera system universal by having all cameras capture images of the same object from different perspectives simultaneously. The correspondence information links locations across all images, allowing a single multi-camera system to perform comprehensive damage detection that would otherwise require multiple separate inspection systems.
Solution Approach 2:
The patent introduces correspondence information as an intermediary that connects images from multiple cameras. This intermediary data structure links locations across different images, enabling the system to process multiple camera inputs systematically and accurately identify damage without requiring complex direct integration of all camera systems.
3Measurement precision
If correspondence information is determined to link locations on different images, then damage localization precision improves, but processing time increases
Solution Approach 1:
The patent performs preliminary action by pre-establishing correspondence information that links locations across multiple images before damage detection begins. This pre-computed spatial mapping allows the system to quickly locate and identify damage by simply comparing image data against the pre-established correspondence structure, rather than computing relationships in real-time during inspection.
Data Source
AI summary
Images may be captured from a plurality of cameras of an object moving along a path. Each of the cameras may be positioned at a respective identified location in three-dimensional space. Correspondence information for the plurality of images linking locations on different ones of the images may be determined. Linked locations may correspond to similar portions of the object captured by the cameras. A portion of the plurality of images may be presented on a display screen via a graphical user interface. The plurality of images may be grouped based on the correspondence information.