Image-Based Parking Space Detection Using 3-Layer Semantic Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current parking space detection methods, such as sensor-based and mechanical control systems, are inefficient, costly, and prone to errors due to environmental factors like light and temperature changes, and fail to provide integrated services like guided parking and surveillance.
Innovation Solution
An image-based space detection system utilizing a 3-layer detection mechanism with a local classification model, adjacent local constraint model, and global semantics model to analyze image data and provide optimized space detection results, capable of handling light changes and occlusions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor-based detection technology is used at each parking space, then detection precision is improved, but device complexity and setup cost increase significantly
Solution Approach 1:
The patent merges multiple sensor detection functions into a single centralized image processing system. Instead of deploying individual sensors at each parking space, the system uses one or more cameras to capture images of multiple parking spaces simultaneously, then processes these images centrally to detect occupancy status across the entire parking area.
Solution Approach 2:
The patent creates a visual copy (image) of the physical parking space status and processes this copy to determine occupancy. The image processing system analyzes captured images to infer the actual state of parking spaces, replacing the need for physical sensors at each location while maintaining detection accuracy.
2Device complexity
If mechanical control based technology is used to count cars, then device complexity is reduced, but measurement precision deteriorates as it cannot detect individual space status
Solution Approach 1:
The patent replaces mechanical counting systems with an optical-based image processing system. Instead of using mechanical bars or counters at the entrance to estimate parking space availability, the system uses cameras and image analysis to directly observe and determine the occupancy status of individual parking spaces, providing precise location information.
3Ease of manufacture
If traditional image analysis methods are used for space detection, then setup cost is reduced, but reliability deteriorates due to sensitivity to light and climate changes
Solution Approach 1:
The patent transforms the image processing approach by changing the parameters being analyzed. Instead of relying on absolute pixel intensity values that are sensitive to lighting conditions, the system detects edges, contours, and geometric features of vehicles and parking space boundaries. These structural parameters remain relatively stable under varying light and climate conditions, improving reliability while maintaining low setup costs.
Data Source
AI summary
Disclosed is a system and method of image-based space detection. The system includes an image selection module, a 3-layer detection mechanism and an optimization module. At least one image processing area that may affect space-status judgment is selected from plural image processing areas. The 3-layer detection mechanism having an observation layer, a labeling layer, and a semantic layer observes the information about the selected image processing area, associates with a local classification model, and adjacent local constraint model and a global semantics model to completely describe the probability distribution of the links among the three layers, and provide global label constraint information. The optimization module analyzes the probability distribution and global label constraint information, and generates an image-based optimized space detection result.