Moving Vehicle Signal Detection via Candidate Region Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current vehicle-mounted recording systems (VMRS) cannot automatically detect the location and color of signal structures, particularly in challenging weather or lighting conditions, which hinders accident investigations and rail system safety.
Innovation Solution
A method and system that utilize a camera-mounted on a moving vehicle to capture images, restrict the search space by defining candidate regions, extract features, and classify them using a trained classifier to detect signal structures and their colors, incorporating camera calibration and tracking algorithms to eliminate false detections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a standard VMRS system continuously records events, then accident evidence is captured, but automatic detection of signal structure location and color is not achieved
Solution Approach 1:
The patent segments the image processing task into distinct stages: candidate region identification, feature extraction, and classification. By dividing the complex detection task into manageable segments, the system achieves automatic signal detection while maintaining processing efficiency.
Solution Approach 2:
The system performs preliminary actions by pre-defining candidate regions where signal structures are likely to appear before full classification. This preliminary filtering step prepares the data in advance, enabling automatic detection to proceed more effectively.
2Reliability
If the entire image is searched for signal structures, then detection coverage is maximized, but processing time and computational load increase
Solution Approach 1:
The patent segments the search space into candidate regions based on prior knowledge of signal structure locations. This segmentation maintains detection reliability by focusing on relevant areas while reducing processing time by excluding irrelevant regions from full analysis.
Solution Approach 2:
The system applies partial action by performing complete feature extraction and classification only on candidate regions rather than the entire image. This approach achieves sufficient detection accuracy for the critical areas while significantly reducing overall processing time.
3Measurement precision
If feature extraction is performed on the entire image, then all potential signals are captured, but computational complexity increases
Solution Approach 1:
The patent segments the image into candidate regions and non-candidate regions, applying different processing complexities to each. This segmentation maintains measurement precision for potential signals while reducing device complexity by limiting intensive feature extraction to only necessary areas.
4Ease of operation
If detection is performed without tracking, then individual frame analysis is simple, but false detections increase
Solution Approach 1:
The patent implements tracking to maintain continuity of detection across multiple video frames. This continuous action reduces false detections by verifying signal presence over time while preserving the relative simplicity of individual frame analysis through consistent tracking logic.
Data Source
AI summary
The present invention aims at providing a method for detecting a signal structure from a moving vehicle. The method for detecting signal structure includes capturing an image from a camera mounted on the moving vehicle. The method further includes restricting a search space by predefining candidate regions in the image, extracting a set of features of the image within each candidate region and detecting the signal structure accordingly.