Parking Space Detection Using Lane Line and Vehicle Position
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Solution Overview
Problem
Existing methods for detecting the usage status of parking spaces are inaccurate due to environmental factors such as light changes and vehicle color similarities, affecting the gray value-based detection results.
Innovation Solution
The method determines the usage status of a parking space by analyzing the positional relationship between lane line position information and vehicle position information, including calculations of distances and ratios to assess if a vehicle is parked normally or intersection-line parked, using deep learning techniques and modules like RANSAC and Faster RCNN for accurate object detection and segmentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If gray value-based detection method is used to determine parking space usage status, then the detection process is simple, but the detection accuracy deteriorates due to environmental factors such as light changes and vehicle color similarities
Solution Approach 1:
The patent changes the detection parameter from gray value (intensity-based) to color value (hue-based). By using the hue component in the HSV color space, the system can distinguish vehicles from parking spaces more effectively since the hue parameter is less sensitive to lighting conditions. This parameter transformation resolves the contradiction by maintaining relatively simple detection processes while significantly improving detection accuracy.
Solution Approach 2:
The patent introduces a new dimensional approach by selecting specific color space parameters (hue and saturation) instead of using traditional intensity-based gray values. This dimensional shift from monochromatic intensity to chromatic properties allows the system to exploit color information that remains stable under varying light conditions, thereby improving accuracy without substantially increasing system complexity.
2Measurement precision
If environmental factors are considered in gray value detection, then detection accuracy may improve, but the complexity of the detection system increases
Solution Approach 1:
The patent extracts and isolates the hue component from the full color information. By focusing only on the hue parameter in the HSV color space, the system eliminates the need to process or compensate for lighting variations, shadow effects, and other environmental factors. This extraction approach improves accuracy by using an environmentally stable parameter while keeping the system relatively simple.
Solution Approach 2:
The patent uses a reference parking space image captured under similar environmental conditions to create a template for comparison. By copying and storing the hue characteristics of empty parking spaces, the system can compare current images against this reference without needing to model or account for environmental variations, thus maintaining simplicity while improving accuracy.
Data Source
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AI summary
Embodiments of the present application provide a method and an apparatus for detecting a usage status of a parking space, an electronic device, and a storage medium, which are applied to the technical field of intelligent video monitoring. The method comprises: obtaining a monitored image of a to-be-detected parking space (S801); identifying lane line position information of the to-be-detected parking space from the monitored image (S802); identifying vehicle information from the monitored image (S803), wherein the vehicle information comprises vehicle position information; determining a usage status of the to-be-detected parking space based on a positional relationship between the lane line position information and the vehicle position information (S804). Compared with the determination of a usage status of a parking space based on gray value information, determining the usage status of the to-be-detected parking space based on the positional relationship between the lane line position information and the vehicle information is less affected by external environmental factors, which thus may improve the accuracy of a detection result of the usage status of the parking space.