Vehicle Classification via Laser Rangefinder and Image Segmentation
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Solution Overview
Problem
Current automated traffic monitoring systems are unable to differentiate between various classes of vehicles, leading to undetected violations of speed and lane restrictions, as they are triggered by speed alone and lack the capability to classify vehicles based on size or type.
Innovation Solution
A system that uses an image capture device and a rangefinder to capture sequential images of vehicles, segment the vehicle from the background, and convert image data to real-world dimensions for classification, comparing these dimensions to a database of vehicle attributes to determine the vehicle's class and enforce traffic regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current automated speed monitoring systems use only speed detection devices (sensors, RADAR, Laser), then the system is simple and can detect speed violations, but it cannot differentiate between vehicle classes and enforce variable speed restrictions or lane prohibitions
Solution Approach 1:
The patent combines image capture devices with rangefinder devices to create a unified system that can both capture vehicle images and measure distances. This merging enables the system to extract vehicle dimensions from images and classify vehicles automatically, resolving the contradiction by integrating multiple functions into a single system that achieves both simplicity and enhanced capability.
Solution Approach 2:
The system uses a single image capture device to perform multiple functions: capturing vehicle images, extracting vehicle dimensions through image processing, and enabling vehicle classification. This multi-functionality allows the system to enforce various traffic regulations (speed limits, lane restrictions, vehicle size restrictions) without requiring separate specialized devices for each function.
2Measurement precision
If the system captures sequential images and processes them to extract vehicle dimensions, then vehicle classification accuracy is improved, but image processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by capturing sequential images at regular time intervals and pre-processing them to extract vehicle dimensions before classification is needed. This allows the system to have ready-to-use vehicle dimension data when classification is required, reducing real-time processing delays while maintaining measurement accuracy through the sequential capture and extraction process.
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
Enables accurate vehicle classification and enforcement of traffic laws by distinguishing between different vehicle types based on size and type, ensuring compliance with speed and lane restrictions, thereby improving the effectiveness of automated traffic monitoring.
Implementation Method 1
a rangefinder device that is collocated with the image capture device simultaneously determines the distance between the vehicle and the image capture device
Data Source
AI summary
An image capture device captures a plurality of sequential images of a vehicle in motion. At substantially the same time a collocated rangefinder determines the distance between the vehicle and the image capture device. Each of the plurality of images may be segmented based on the rangefinder point of reference. The portion of each image representing the vehicle is extracted based on its motion with respect to a stationary background. Knowing the size of the vehicle with respect to the image and the distance that the vehicle is from the image capture device, the image data is converted to real world dimensions. Using these real world dimensions a vehicle classification is determined.