Lane Separation Equipment Identification Using Multi-Algorithm Image Analysis
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Solution Overview
Problem
Existing map generation devices face challenges in accurately identifying lane separation equipment, such as separation poles and wire ropes, in two-way traffic sections, due to the difficulty in detecting the presence or absence of wire ropes from images, which is crucial for maintaining safety during accidents.
Innovation Solution
A feature identification device that employs multiple algorithms to identify lane separation equipment based on images captured by a vehicle-mounted camera, using pre-trained detectors and classifiers to differentiate between separation poles and wire ropes, especially in two-way traffic sections, by analyzing the presence and continuity of wire ropes between poles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wire ropes are detected from images to identify lane separation equipment type, then identification accuracy improves, but detection difficulty increases due to the long and narrow shape with small diameter
Solution Approach 1:
The patent transforms the detection problem from direct 2D image analysis to a multi-step process involving candidate region extraction, pole detection, and wire rope region determination based on spatial relationships between detected poles. This dimensional transformation allows the system to leverage the structured arrangement of poles to infer wire rope locations, making the detection of thin wire ropes feasible.
Solution Approach 2:
The patent performs preliminary detection of pole candidates and determines wire rope candidate regions before final identification. By pre-establishing the spatial framework through pole detection and defining candidate regions where wire ropes should appear, the system prepares the detection task in advance, reducing the difficulty of directly detecting thin wire ropes in the final identification stage.
2Reliability
If multiple algorithms are used to identify lane separation equipment in two-way traffic sections, then identification certainty improves, but processing complexity increases
Solution Approach 1:
The patent divides the identification process into distinct algorithmic stages: candidate separation strip information detection, pole candidate detection, wire rope candidate region determination, and final type identification. Each stage processes specific aspects of the problem independently, allowing the system to achieve high reliability through multiple checks while managing complexity through modular processing.
Solution Approach 2:
The patent implements dynamic processing where the identification algorithm adapts its complexity based on the detection context. The system determines whether wire rope candidate regions exist based on pole arrangements, and only performs detailed wire rope detection when necessary. This dynamic approach ensures high identification certainty for critical cases while avoiding unnecessary processing complexity in simpler scenarios.
Data Source
AI summary
A feature identification device identifies a type of lane separation equipment, including at least separation poles and separation wire ropes, for separating a road by travel direction. When the type of lane separation equipment is not associated with a predetermined position on the road, the device identifies the type of the lane separation equipment based on an image in which the lane separation equipment is captured at a predetermined position by an algorithm selected from a first algorithm and a second algorithm based on whether the predetermined position is included in the two-way traffic section. When the predetermined position is included in the two-way traffic section, the device identifies the type of the lane separation equipment using the second algorithm which is capable of identifying separation poles and separation wire ropes with higher certainty than the first algorithm.