Lane Departure Warning Using Image Segmentation and Angle Variation
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Solution Overview
Problem
Conventional lane departure warning systems struggle to detect various types of lane lines and provide real-time warnings due to limitations in edge detection algorithms, which require multiple frames for analysis and often result in erroneous detection of lane markers, especially for lane lines with subtle brightness gradients and short lane lines.
Innovation Solution
A method and system that segment images into regional areas, analyze characteristics to identify lane line candidates, distinguish left and right lane lines based on angle variations, and send warnings when lane departure is detected, utilizing image segmentation and gradient analysis to enhance detection accuracy and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional edge detection algorithms are used to detect lane markers, then edge pixels can be detected, but the detected edge is just the edge of a lane marker causing hollow line results and requiring additional processing steps
Solution Approach 1:
The patent segments the image processing task into distinct stages: edge detection to identify candidate pixels, followed by curve fitting to connect these pixels into continuous lane lines. This segmentation resolves the hollow line problem by adding the curve fitting step that fills in the gaps between detected edges.
Solution Approach 2:
The patent performs preliminary edge detection to identify candidate pixels before performing the main curve fitting operation. By pre-identifying edge pixels and their coordinates, the system prepares data structures in advance that facilitate efficient lane line reconstruction, reducing the need for additional processing steps.
2Reliability
If conventional edge detection algorithms are used, then lane markers with sharp brightness gradients can be detected, but lane markers with subtle brightness gradients cannot be detected
Solution Approach 1:
The patent adjusts detection parameters dynamically based on image characteristics. By calculating the standard deviation of pixel intensities and adapting the edge detection threshold accordingly, the system can detect both high-contrast and subtle lane markers. The curve fitting process also adapts to different lane marker styles by adjusting the polynomial order and fit criteria.
3Measurement precision
If conventional edge detection algorithm is used to process short lane lines, then additional pre-processing steps are required to ensure detection ability, but this increases processing complexity
Solution Approach 1:
The patent merges the edge detection and lane line detection processes by using the same edge detection results for both identifying lane markers and constructing lane lines. The curve fitting operation directly connects detected edge pixels without requiring separate pre-processing steps for short lane lines, simplifying the overall workflow.
4Quantity of substance
If conventional line detection method is used, then the number of straight lines can be known, but the region corresponding to each straight line cannot be further known
Solution Approach 1:
The patent transitions from detecting simple line parameters to identifying spatial regions by fitting curves to edge pixels and determining the area enclosed by these curves. This dimensional extension from 1D line detection to 2D region identification preserves both the number of lines and their spatial locations, enabling the system to distinguish lane lines from other linear features.
5Reliability
If lane departure algorithm analyzes multiple continuous frames to judge vehicle moving direction, then lane departure can be detected, but time delay exists before detection result is obtained
Solution Approach 1:
The patent performs preliminary lane line detection and vehicle position calculation in advance, preparing data structures and intermediate results before the actual lane departure judgment is needed. By pre-processing the image data and maintaining buffers of recent frames, the system reduces the computational burden during real-time decision-making, minimizing detection delay.
Solution Approach 2:
The patent maintains continuous processing of image frames by always having recent data available in memory buffers. Instead of waiting to accumulate multiple frames before starting analysis, the system continuously processes incoming frames and maintains ready-to-use data structures, ensuring that lane departure detection can proceed immediately when needed.
Data Source
AI summary
A method and a system for lane departure warning are provided. The method is as follows. An original image is segmented into a plurality of regional images. Next, characteristics of each regional image are analyzed, and accordingly non-lane line regions are removed from the regional images, so as to obtain a plurality of lane line candidates. Then, a plurality of lane lines are determined from the lane line candidates according to a location of each lane line candidate in the original image. Finally, the lane lines are distinguished into left lane lines and right lane lines, and a variation of an angle between each left lane line and a horizontal line and a variation of an angle between each right lane line and the horizontal line are analyzed, so as to judge whether a vehicle departs from a lane and send a lane departure warning.