Vehicle Collision Detection via Pixel Intensity Change Analysis
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Solution Overview
Problem
Current systems fail to effectively detect object collisions with parked vehicles, particularly when the offending vehicle does not leave information or when collisions go unnoticed, leading to unresolved damage and responsibility issues.
Innovation Solution
A system utilizing a processor and camera sensor to capture sequential images, determining a change amount in pixel intensity values between images to detect if an object is approaching or has collided with the vehicle, with thresholds for approaching and collision detection, and communicating identifying information to a remote device upon collision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual damage reporting is used when a vehicle is parked, then the system is simple and easy to implement, but it fails to detect collisions when the offending vehicle does not leave information or when collisions go unnoticed
Solution Approach 1:
The system performs preliminary actions by capturing images of the scene before a collision occurs and storing baseline pixel intensity data. When a collision happens, the system compares post-collision images against these pre-captured baselines to automatically detect damage without requiring manual reporting or the offending vehicle to leave information.
Solution Approach 2:
The patent replaces manual mechanical reporting systems with an automated optical detection system using camera sensors and image processing algorithms. The system uses pixel intensity analysis to automatically detect collisions, substituting human intervention and physical note-taking with electronic image capture and computational analysis.
2Measurement precision
If automated image analysis is implemented to detect collisions, then collision detection accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system extracts only the essential information needed for collision detection by analyzing pixel intensity changes at specific locations in the image. Rather than processing entire high-resolution images, the system focuses on extracting relevant pixel data that indicates collision occurrence, thereby reducing computational overhead while maintaining detection accuracy.
3Reliability
If continuous monitoring is performed to detect approaching objects, then real-time collision warning is achieved, but energy consumption increases
Solution Approach 1:
The system implements periodic action by capturing images at specific time intervals rather than continuously monitoring. The camera sensor takes snapshots periodically, and the system analyzes these discrete images for pixel intensity changes indicating approaching objects or collisions. This periodic sampling approach provides real-time collision warning capability while significantly reducing energy consumption compared to continuous monitoring.
Data Source
AI summary
A system for detecting an object collision includes a processor and a memory in communication with the processor with an objection collision detection module. The objection collision detection module has instructions that, when executed by the processor, cause the processor to obtain a first image and a second image of a scene from a camera sensor mounted to a vehicle, determine a change amount between the first image and the second image, and based on the change amount, determine at least one of that an object is approaching the vehicle or the object has collided with the vehicle. The change amount represents the number of pixels with the same location value that changed intensity values between the first and second images.