Parking Frame Detection Using Provisional Marker Alignment
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Solution Overview
Problem
Existing image processing systems for parking assistance struggle to accurately identify parking frames based on corner markers, particularly when the rear-end line of a parking section is used for alignment, as the corner markers at the rear corner are often less clearly imaged compared to those at the front corner.
Innovation Solution
An image processing device and method that employs a camera-mounted vehicle to detect corner markers on both ends of a parking frame using edge detection, sets a provisional frame based on front corner markers, and identifies the parking frame by detecting and verifying corner markers along the sidelines of the provisional frame, ensuring accurate alignment with the rear-end line.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If corner markers at rear corner are used for parking frame identification, then parking alignment accuracy with rear-end line is improved, but detection reliability deteriorates due to less clear imaging
Solution Approach 1:
The system first detects corner markers at the front corner to establish a provisional parking frame before attempting to detect markers at the rear corner. This preliminary action creates a reference framework that guides subsequent detection efforts and provides fallback options if rear corner markers are not clearly detected.
Solution Approach 2:
The provisional parking frame acts as an intermediary element between the clearly detected front corner markers and the poorly detected rear corner markers. By establishing this intermediate reference structure, the system can infer rear corner positions and parking frame boundaries even when direct detection of rear markers is unreliable.
2Measurement precision
If edge detection is performed across the entire image to detect all corner markers, then detection completeness is improved, but computational load increases
Solution Approach 1:
Instead of applying edge detection uniformly across the entire image, the system focuses detection efforts on specific local regions - primarily around the provisional parking frame boundaries. This localized approach maintains detection effectiveness while significantly reducing the computational area that needs to be processed.
Solution Approach 2:
The detection process is segmented into distinct phases: first detecting front corner markers, then establishing a provisional frame, and finally searching for rear corner markers only in regions defined by this provisional frame. This segmentation divides the computational task into manageable segments rather than processing the entire image at once.
Data Source
AI summary
An image processing device includes a camera configured to be mounted on a vehicle to capture an image around the vehicle, a marker detector to carry out an edge detection process on the image to detect corner markers on one end of a parking frame, a provisional parking frame setting part to set a provisional parking frame based on the detected corner markers on the one end, and a parking frame identifying part to identify the parking frame. The marker detector is configured to detect corner markers on another end of the parking frame in directions along sidelines of the provisional parking frame, and the parking frame identifying part is configured to identify the parking frame based on the corner markers on the one end and the corner markers on the other end.