Vehicle Sunvisor State Detection Using Image Feature Matching
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Solution Overview
Problem
Current methods for detecting a vehicle sunvisor's state at night are inefficient and prone to false detections due to road texture and environmental factors, making them unsuitable for practical application in vehicle security systems.
Innovation Solution
A method involving gray-scale preprocessing, extraction of main connected regions and horizontal long edges, and feature matching to determine the sunvisor's state using geometric features and rectangle similarity, effectively reducing the influence of road texture and environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing detection methods are used at night, then detection can be performed, but detection precision deteriorates due to road texture and environmental factors
Solution Approach 1:
The patent segments the image processing into distinct stages: gray-scale preprocessing, main connected region extraction, horizontal long edge extraction, and feature matching. This segmentation allows each stage to address specific aspects of the detection problem, with gray-scale preprocessing specifically targeting the removal of road texture influences while preserving sunvisor features.
Solution Approach 2:
The patent extracts and removes harmful factors through gray stretching and mathematical morphology operations that specifically target and eliminate road texture patterns. It also extracts key features (main connected regions and horizontal long edges) from the image for subsequent matching and identification of sunvisor state.
2Ease of operation
If simple detection algorithms are used, then ease of operation improves, but detection precision deteriorates due to false detections of similar-shaped objects
Solution Approach 1:
The patent combines multiple detection criteria into a unified approach: region-based features (main connected regions), edge-based features (horizontal long edges), geometric features, and rectangle similarity measures. This merging of multiple independent verification mechanisms maintains operational simplicity while significantly improving detection precision by cross-validating results.
Solution Approach 2:
The patent replaces simple mechanical detection with image processing techniques including gray-scale transformation, mathematical morphology, and feature matching algorithms. This substitution enables more sophisticated detection that distinguishes sunvisors from similar-shaped objects through multi-parameter analysis rather than simple shape matching.
3Measurement precision
If complex processing steps are added to improve detection precision, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent performs preliminary gray-scale preprocessing and edge extraction before the main detection process. These preliminary actions simplify subsequent processing by pre-processing the image data, removing road texture influences, and identifying candidate regions in advance, thereby reducing the complexity of the main detection algorithm.
Solution Approach 2:
The patent changes image parameters through gray stretching and mathematical morphology operations to transform the image into a form more suitable for detection. By adjusting parameters like gray level distribution and applying morphological operations, the system simplifies the detection task while improving precision.
Data Source
AI summary
A method for detecting a vehicle sunvisor's state includes obtaining a detected image; conducting a gray-scale preprocessing on the detected image, to obtain a gray-level image; conducting a main connected region extraction on the gray-level image, and calculating a geometric feature and a rectangle similarity of each main connected region; conducting a horizontal long edge extraction on the gray-level image, and conducting feature matching operation between horizontal long edges and main connected regions to obtain a region edge matching relationship; determining the sunvisor's state based on the region edge matching relationship, the geometric feature of main connected regions and rectangle similarity of main connected regions. The present invention can be widely applied in the field of image process.