Lane Stripe Image Analysis Using Directional Segmentation
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Solution Overview
Problem
Automatic driving technology faces challenges in real-time traffic state detection due to varying traffic conditions, requiring high-performance data processing that increases the cost of automatic driving assistance systems.
Innovation Solution
An image analysis method and device that sets a reference point to recognize lane stripe images in multiple directions, defines preset sections, determines characteristic values, and calculates feature parameters to derive actual lane parameters related to environmental messages, using a projection computing module, processing module, and determination module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-performance data processing is used to achieve real-time traffic state detection, then detection accuracy is improved, but system cost increases
Solution Approach 1:
The patent divides the lane detection task into multiple directional analyses (first direction, second direction, third direction) with different complexity levels. The system segments the problem by analyzing lane stripes in multiple directions rather than attempting a single comprehensive analysis, reducing the computational burden while maintaining detection accuracy.
Solution Approach 2:
The system performs partial analysis by focusing on specific directional components of lane stripes rather than analyzing all possible features simultaneously. By selecting and analyzing only the necessary directional components (first, second, and third directions), the system achieves adequate detection accuracy with reduced processing complexity.
2Measurement precision
If complicated data processing is performed to meet various automatic driving requirements, then determination accuracy is improved, but calculation speed decreases
Solution Approach 1:
The patent segments the data processing into distinct directional analyses (first direction for width, second direction for angle, third direction for curvature). This segmentation allows each analysis to focus on specific features, improving determination accuracy for each parameter while enabling parallel or sequential processing that maintains calculation speed.
Solution Approach 2:
The system performs preliminary directional analysis on lane stripe images before final determination. By pre-processing the images to extract directional features (width, angle, curvature) in separate steps, the system prepares data in advance for the final determination stage, improving both accuracy and processing efficiency.
3Measurement precision
If multiple directional analysis is performed on lane stripe images, then lane parameter accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent divides the lane parameter measurement into three separate directional analyses: first direction for lane width, second direction for lane angle, and third direction for lane curvature. This segmentation reduces processing complexity by handling each parameter independently rather than attempting simultaneous multi-parameter analysis.
Solution Approach 2:
The system performs analysis in three specific directions rather than attempting exhaustive analysis in all possible directions. This partial action approach focuses computational resources on the three most relevant directional components for lane parameter determination, achieving adequate accuracy without excessive processing complexity.
Data Source
AI summary
An analysis method of lane stripe images, an image analysis device and a non-transitory computer readable medium thereof are provided to perform steps of: setting a reference point as a center to recognize the lane stripe image in a plurality of default directions; defining a plurality of preset sections onto the lane stripe image and determining a characteristic value of the lane stripe image in each of the preset sections whenever the lane stripe image is recognized in one of the default directions; determining a first feature parameter according to the characteristic values of the lane stripe image in the preset sections when the lane stripe image is recognized in at least one of the default directions; and determining an actual lane parameter of the lane stripe image according to at least the first feature parameter.