Vehicle-Mounted Orthomosaic System for Pavement Defect Detection
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Solution Overview
Problem
Current pavement monitoring systems using drones and satellites are inadequate due to limitations in image resolution and the presence of obstacles like tree canopies, resulting in high costs and incomplete imaging, making them unsuitable for effective defect detection and measurement.
Innovation Solution
A surface defect monitoring system utilizing a high-resolution camera mounted on a land vehicle to capture images, which are then processed to create ortho-rectified imagery and orthomosaics, enabling the detection and classification of pavement flaws through artificial intelligence, along with the generation of three-dimensional imagery and surface maps, allowing for remote assessment and maintenance planning without on-site inspections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If drones or satellites are used for pavement monitoring, then coverage area is increased, but image resolution deteriorates and obstacles like tree canopies block imaging
Solution Approach 1:
The patent introduces a land vehicle as an intermediary platform between satellites/drones and the pavement surface. The vehicle-mounted camera system captures high-resolution images at ground level, avoiding obstacles like tree canopies that block aerial imaging, while the vehicle's movement provides extensive coverage area.
2Measurement precision
If high-resolution cameras are mounted on land vehicles, then image resolution and defect detection capability are improved, but equipment cost and complexity increase
Solution Approach 1:
The land vehicle platform is designed with multi-functionality, serving both as a transportation means and a mobile imaging platform. The camera system can capture images of various infrastructure elements (pavement, bridges, railroads), and the orthomosaic technology can generate multiple product types (2D maps, 3D models, defect reports), reducing the need for specialized equipment for each application.
3Measurement precision
If manual on-site inspections are conducted, then detailed defect assessment is achieved, but time consumption and labor costs increase
Solution Approach 1:
The patent replaces manual mechanical inspection processes with an automated imaging and processing system. The land vehicle-mounted camera captures images, which are then automatically processed through orthorectification, orthomosaic generation, and AI-based defect detection algorithms, eliminating the need for manual on-site inspection while maintaining or improving assessment accuracy.
4Area of stationary object
If satellite imagery is used for pavement monitoring, then coverage area is increased, but image resolution and ability to detect small defects deteriorates
Solution Approach 1:
The patent segments the monitoring process into multiple stages: (1) capturing high-resolution images at ground level using vehicle-mounted cameras, (2) processing images through orthorectification to correct geometric distortions, (3) generating orthomosaics by stitching multiple images, and (4) performing defect detection and measurement. This segmentation allows achieving both high resolution for small defects and extensive coverage through the vehicle's movement and image stitching.
Data Source
AI summary
A system for taking high-resolution photographs from a vehicle-mounted camera, forming orthomosaics from video and/or multiple high-resolution photographs, and using artificial intelligence to detect and classify pavement flaws and defects in the imagery. Detection also includes the ability to capture quantifiable metrics for the defects and/or a region of interest. Three-dimensional imagery is produced from the same images as the orthomosaics. Surface and terrain map products made from the same source images capture additional details such as depth and volume. The highlighted orthomosaics and three-dimensional imagery can then be used as a basis to determine the pavement surface condition and subsequently support maintenance orders and manage pavement repairs. Further, metadata such as latitude, longitude, and altitude geo-location coordinates and sampling time can also be transferred to the output products to create a digital time history and enable analysis for preventative maintenance planning. Alternatively-sourced imagery may also be analyzed.