Lane Detection Apparatus Using Segmented Hough Transform
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Solution Overview
Problem
Existing lane detection systems face challenges in processing speed, leading to delayed warnings for lane departure, which can increase the risk of accidents.
Innovation Solution
An operating method for a lane detection apparatus that sets regions of interest based on the horizontal location of a vehicle in a driving lane, using Hough transform to detect edges and generate Hough spaces, thereby accelerating the lane detection process and enabling rapid warnings for lane departure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire driving image is processed for lane detection, then the detection accuracy is improved, but the processing time increases
Solution Approach 1:
The patent divides the driving image into multiple regions of interest (ROIs) based on the vehicle's horizontal location in the driving lane. By segmenting the image processing task into specific ROIs rather than processing the entire image, the system maintains lane detection accuracy while significantly reducing the computational load and processing time.
Solution Approach 2:
The patent applies different processing quality levels to different regions of the image. Regions of interest that are more critical for lane detection receive higher processing priority and more computational resources, while other areas are processed with lower priority or skipped entirely. This local quality approach ensures accurate lane detection in critical areas while reducing overall processing time.
2Reliability
If traditional Hough transform is applied to the entire image, then all potential lanes are detected, but the processing speed decreases
Solution Approach 1:
The patent segments the Hough transform processing by applying it only to specific regions of interest rather than the entire image. This segmentation allows the system to maintain reliability in detecting actual lanes while dramatically improving processing speed by limiting the transform operation to relevant image portions.
Solution Approach 2:
The patent employs partial action by applying the Hough transform only to necessary regions of interest rather than performing exhaustive processing on the entire image. This partial processing approach is sufficient for detecting lanes in the vehicle's current context while achieving the required processing speed for real-time warnings.
3Reliability
If the region of interest is expanded to cover the entire image, then no lane is missed, but the processing efficiency decreases
Solution Approach 1:
The patent implements local quality by identifying and processing only the specific regions of interest that are relevant to the vehicle's current lane position. This approach ensures that the most critical areas for lane detection receive full processing attention, maintaining reliability while improving processing efficiency by avoiding unnecessary computation in irrelevant areas.
Solution Approach 2:
The patent performs preliminary action by first determining the vehicle's horizontal location and pre-identifying the regions of interest before applying the Hough transform. This preliminary step allows the system to focus computational resources on the most relevant areas, ensuring that actual lanes are not missed while significantly improving processing efficiency.
Data Source
AI summary
Disclosed are a lane detection apparatus and an operating method for the same, and the operating method for the lane detection apparatus includes: detecting a plurality of edges in a driving image of a vehicle expressed by Cartesian coordinates; detecting a pattern of the plurality of edges; estimating a horizontal location of the vehicle in a driving lane based on the detected pattern; setting two regions of interest in the driving image based on the horizontal location; generating two Hough spaces corresponding two regions of interest, respectively, including a plurality of counting regions, and expressed by polar coordinates; calculating a polar coordinate value of each pixel included in the edge shown in each of two regions of interest among the plurality of edges by using Hough transform that transforms the Cartesian coordinates into the polar coordinates; accumulating the count of the counting region to which the polar coordinate value belongs, with respect to two respective Hough spaces; selecting a counting region having the highest count number among the plurality of counting regions with respect to two respective Hough spaces; transforming the counting region having the highest count number into two straight lines expressed by the Cartesian coordinates, with respect to two respective Hough spaces; and detecting two transformed straight lines as a left lane and a right lane of the driving lane.