Crash Test Vehicle Image Fusion Evaluation Unit
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Solution Overview
Problem
Current crash test vehicle measurement systems are partially automated and struggle with varying reflection behaviors of different vehicle materials, leading to suboptimal image quality and manual intervention in data processing.
Innovation Solution
An evaluation unit with image fusion capabilities, combined with a database for CAD data and self-learning algorithms, enables fully automated high-quality image data processing by optimizing and fusing images from multiple sensors with different recording types, and using shade detection software to improve data quality and camera positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple measurement sensors with different recording types are used to capture measurement areas, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple measurement sensors with different recording types (e.g., optical, laser, tactile) into a single integrated measurement system. The evaluation unit fuses data from these diverse sensors to achieve comprehensive and high-precision measurement of vehicle components, resolving the contradiction by merging multiple complex elements into a coordinated system that delivers superior measurement quality.
Solution Approach 2:
The evaluation unit is designed with multi-functional capabilities to process and evaluate data from various sensor types simultaneously. It can handle optical images, laser scans, and tactile measurement data through a single platform, reducing the need for separate specialized systems and thereby managing device complexity while maintaining high measurement precision across different measurement areas.
2Productivity
If fully automated image processing is implemented, then productivity is improved, but measurement precision may deteriorate due to lack of manual verification
Solution Approach 1:
The evaluation unit incorporates feedback mechanisms that automatically verify and validate processed measurement data. The system compares results against predefined quality criteria and previous measurement data, providing continuous feedback to adjust processing parameters and ensure measurement precision is maintained throughout the automated process without requiring manual intervention at each step.
Solution Approach 2:
The system performs self-verification and quality control through automated algorithms that check measurement consistency and accuracy. The evaluation unit independently validates its own processing results by comparing against reference data and detecting anomalies, enabling fully automated operation while maintaining high measurement precision through self-correcting capabilities.
3Ease of operation
If manual marking and photo capture are used, then ease of operation is maintained, but loss of time increases due to extensive manual data processing
Solution Approach 1:
The system performs preliminary automated processing of measurement data immediately after capture, including initial alignment, feature detection, and preliminary evaluation. This preliminary action reduces the burden of subsequent manual processing while maintaining ease of operation, as operators only need to review and approve results rather than perform extensive manual analysis.
Solution Approach 2:
The patent replaces manual mechanical marking and photo capture processes with automated sensors and imaging systems. The measurement system automatically captures and processes data without requiring manual marking of vehicle components or manual photo taking, thereby eliminating time-consuming manual operations while keeping the system easy to operate through automated workflows.
4Device complexity
If measurement areas with varying reflection behaviors are measured uniformly, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The evaluation unit applies local quality principles by automatically detecting and adapting to the specific properties of different measurement areas. The system identifies varying reflection behaviors (metallic, glossy, matte, transparent) and applies tailored processing algorithms to each local region, ensuring high measurement precision for each material type without requiring a completely complex customized system for each area.
Solution Approach 2:
The system dynamically changes processing parameters based on the detected properties of each measurement area. When different reflection behaviors are detected, the evaluation unit automatically adjusts imaging parameters, lighting conditions, and processing algorithms to optimize measurement precision for that specific local area, maintaining simple overall system architecture while achieving high precision through adaptive parameter changes.
Data Source
AI summary
An evaluation unit is provided for processing images and/or image sequences of measurement areas (8, 10, 12, 14, 16, 18) that are detectable on a crash test vehicle (4). Transmitted images and/or image sequences from at least one measurement sensor are utilizable. Additionally, image fusion apparatus is provided to produce digital image fusion of images and/or image sequences as image data (38, 40) of the same measurement area (8, 10, 12, 14, 16, 18). An evaluation method, a measurement system for a crash test vehicle measurement and a method for performing a crash test vehicle measurement also are provided.