Vehicle Speed Estimation Through Predictive Road-Marker Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image processing methods for vehicle speed determination are computationally expensive due to the use of orthogonal wavelets, making them unsuitable for real-time applications with limited processing power, especially under varying lighting conditions.
Innovation Solution
A modified discrete wavelet transform (DWT) approach using symmetrical, integer-valued filters based on Pascal's triangle coefficients is employed to process images of road markers, allowing efficient extraction of low-frequency components and robust detection of unoccupied road areas, reducing computational complexity and enhancing accuracy under varying lighting conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If orthogonal wavelets are used for image processing to determine vehicle speed, then measurement precision is improved, but device complexity and computational cost increase
Solution Approach 1:
The patent changes the parameters of the wavelet transform by using modified discrete wavelet transform with symmetrical, integer-valued filters based on Pascal's triangle coefficients instead of traditional orthogonal wavelets. This parameter change reduces computational complexity while maintaining the ability to extract low-frequency components for accurate speed determination
Solution Approach 2:
The patent employs computationally inexpensive integer-valued filters that can be processed efficiently, replacing expensive orthogonal wavelet computations. These simplified filters achieve sufficient measurement precision for vehicle speed determination without requiring high computational resources
2Measurement precision
If traditional image processing methods are used to detect road markers, then measurement precision is improved, but productivity decreases due to computational expense
Solution Approach 1:
The patent modifies the image processing parameters by using symmetrical integer-valued filters with coefficients based on Pascal's triangle. This enables faster computation while maintaining the precision needed for road marker detection and vehicle speed determination
Solution Approach 2:
The patent performs preliminary action by using the modified DWT to efficiently extract low-frequency components and predict road marker locations before detailed analysis. This preliminary processing reduces the computational burden on subsequent steps, improving overall processing speed
3Reliability
If complex wavelet transforms are applied to process images under varying lighting conditions, then reliability is improved, but use of energy increases
Solution Approach 1:
The patent changes the wavelet transform parameters to use symmetrical, integer-valued filters that are computationally efficient. These modified parameters maintain reliability under varying lighting conditions by preserving the ability to detect road markers while significantly reducing energy consumption
Solution Approach 2:
The patent extracts only the essential low-frequency components needed for road marker detection and speed determination, discarding redundant high-frequency information. This extraction approach maintains measurement reliability while reducing the computational energy required for processing
Data Source
AI summary
An apparatus for determining a speed of a vehicle along a road by processing a first image and a second image of the road captured by a camera on the vehicle and comprising respective road marker images of a road marker, the apparatus arranged to: determine a location of the road marker in the first image; predict a location of the road marker in the second image based on the determined location, an estimate of the vehicle speed, and a time period between capture of the images; detect the road marker in a portion of the second image at the predicted location; estimate a distance moved by the vehicle during the time period based on the determined location, and a location of the detected road marker in the portion of the second image; and calculate the speed based on the estimated distance and the time period.