Stereoscopic Pavement Scanning System for 3D Distress Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current pavement assessment technologies are limited by their inability to accurately detect and measure pavement distresses in real-time at high speeds, as they often rely on 2D imaging or discrete point measurements, which do not effectively capture the full extent and severity of pavement conditions such as cracking, rutting, and texture.
Innovation Solution
A high-speed pavement stereoscopic line scan imaging system that uses multiple stereoscopic image capturing devices and lighting sources mounted on a mobile vehicle, synchronized with positioning sensors, to generate 3D images of the pavement surface, enabling accurate detection and classification of distresses through computer vision and machine learning modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 2D imaging systems are used to capture pavement surface data, then the entire lane area can be captured, but the measurement is two-dimensional and cannot provide accurate three-dimensional elevation information for distress detection
Solution Approach 1:
The patent transitions from 2D imaging to 3D measurement by implementing a stereoscopic vision system using multiple cameras positioned at different heights and angles. This dimensional change enables accurate capture of pavement elevation data, allowing the system to generate three-dimensional point clouds that represent both the horizontal extent and vertical profile of pavement surfaces, thereby resolving the limitation of 2D imaging systems
2Area of stationary object
If profiling systems use laser triangulation to measure elevation at fixed intervals, then 3D profiles can be obtained, but discrete measurements are taken and the entire surface is not measured
Solution Approach 1:
The patent segments the pavement surface into multiple measurement zones by deploying several cameras at different positions (e.g., left, center, right lanes and multiple heights). Each camera captures a specific portion of the surface, and the individual point clouds are subsequently integrated to form a complete three-dimensional representation of the entire pavement area, thus achieving both comprehensive coverage and detailed measurement
3Productivity
If conventional pavement assessment systems are used, then manual or automatic assessment can be performed, but real-time detection and measurement of pavement distresses at high speeds is not achieved
Solution Approach 1:
The patent implements real-time image capture and preliminary processing during vehicle traversal of the pavement. By capturing images continuously at high speed and performing initial processing steps (such as feature detection and point cloud generation) while the vehicle is moving, the system enables immediate assessment of pavement conditions without requiring the vehicle to stop or slow down, thus achieving high-speed productivity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides real-time, high-resolution 3D imaging capable of detecting and classifying various pavement distresses, improving the accuracy and efficiency of pavement condition assessment, enabling timely maintenance and reducing the risk of false positives from environmental factors.
Implementation Method 1
one or more light sources mounted to a mobile vehicle for illuminating a pavement surface
Implementation Method 2
a plurality of positioning sensors mounted to the mobile vehicle, the positioning sensors adapted to encode movement of the mobile vehicle and provide a synchronization signal
Data Source
AI summary
Disclosed is a mobile pavement surface scanning system for detecting pavement distress. In an embodiment the system comprises one or more light sources mounted on the mobile vehicle for illuminating a pavement, one or more stereoscopic image capturing devices mounted on the vehicle for capturing sequential images of an illuminated pavement surface, and a plurality of positioning sensors mounted on the mobile vehicle, the positioning sensors adapted to encode movement of the mobile vehicle and provide a synchronization signal for the sequential images captured by the one or more stereoscopic image capture devices. One or more computer processors are adapted to synchronize the intensity image pairs captured by each camera in the one or more stereoscopic image capturing devices, perform a 3D reconstruction of the pavement from the intensity image pairs using stereoscopic principles, generate a depth image and an intensity image pair from the 3D reconstruction, and process at least one of the depth image and the intensity image utilizing one or more distress detection modules to detect a type of pavement distress.