Traffic Sign Recognition via Local Contrast Enhancement
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Solution Overview
Problem
Existing driver assistance systems face challenges in reliably identifying traffic signs, particularly speed limit signs, due to low image contrast from cameras with limited bit depth, which can lead to missed speed restrictions and unsafe driving.
Innovation Solution
An evaluation facility that locates a predetermined shape in initial image information, requests and records the same image segment with improved contrast, and identifies traffic signs using enhanced image processing techniques such as modified exposure time, amplification, and HDR parameters, allowing for precise recognition of traffic signs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the camera uses limited bit depth to reduce cost and computational burden, then device complexity and energy consumption are reduced, but image contrast deteriorates leading to unreliable traffic sign identification
Solution Approach 1:
The patent applies local quality enhancement by identifying specific image segments containing predetermined shapes (traffic signs) and enhancing contrast only in those regions rather than processing the entire image. This is achieved through shape-based segmentation and localized contrast improvement techniques, which maintain reliability while reducing computational burden.
Solution Approach 2:
The system performs preliminary shape detection and image segment identification before final traffic sign recognition. By pre-locating potential traffic signs based on predetermined shapes in the initial low-contrast image, the system prepares targeted regions for enhanced processing, ensuring reliable identification without full-image high-contrast processing.
2Measurement precision
If the system processes entire images with high contrast to improve traffic sign visibility, then measurement precision improves, but productivity decreases due to increased computational burden
Solution Approach 1:
The patent divides the image processing task into two segments: initial shape detection in the entire image at low computational cost, followed by detailed contrast enhancement and recognition only in identified image segments containing predetermined shapes. This segmentation enables accurate traffic sign recognition while maintaining high processing efficiency.
Solution Approach 2:
Instead of applying full-image high-contrast processing, the system applies contrast enhancement partially only to identified image segments containing traffic signs. This partial action approach achieves the necessary measurement precision for accurate recognition while significantly reducing the computational burden compared to processing entire images.
3Measurement precision
If the system requests new recordings with improved contrast for located image segments, then measurement precision improves, but loss of time increases due to additional recording requests
Solution Approach 1:
The system performs preliminary shape detection in the initial image recording before requesting additional recordings. By identifying potential traffic signs early based on predetermined shapes, the system can selectively request enhanced recordings only for relevant segments, minimizing time loss while ensuring accurate identification.
Solution Approach 2:
The evaluation facility uses the initial low-contrast image to self-identify potential traffic sign locations through shape detection, then uses this information to guide subsequent high-contrast recordings. This self-service approach eliminates the need for complete re-recording, reducing time loss while improving measurement precision.
Data Source
AI summary
An evaluation device for a driver assistance system for a vehicle includes an input for receiving image information recorded by a camera, a first component for locating an image section present in a predefined shape in first image information received from the camera, and a second component for requesting second image information. The second image information corresponds to a renewed image of an image section found by the first component, with improved contrast in relation to the first image information. A third component is present for identifying a traffic sign in the second image information, and an output for emitting a signal relating to a traffic sign identified by the third component. There is also provided a computer program product and a method for operating a driver assistance system.