In-Vehicle Camera Image Selection via Brightness Threshold
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Solution Overview
Problem
Existing in-vehicle camera systems face challenges in efficiently selecting driving images that include license plates, particularly due to variations in lighting conditions, which affect image brightness and lead to background noise, thereby reducing the speed and accuracy of image recognition.
Innovation Solution
The system employs a light compensating unit to capture two driving images, one with supplemental light and one without, and uses a processing unit to select the image based on a brightness difference threshold, dynamically filtering out background noise and enhancing image recognition speed and yield.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple driving images are captured for image recognition, then the accuracy of license plate identification is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary brightness comparison between the first image (captured with supplemental light) and the second image (captured without supplemental light) to determine whether the license plate is visible. This preliminary action filters out images that do not contain visible license plates before performing full image recognition processing, thereby reducing processing time while maintaining identification accuracy
Solution Approach 2:
The patent extracts and utilizes the brightness difference information between two images as a separate criterion for image selection. By taking out the brightness comparison step as an independent filtering mechanism, the system can quickly eliminate unsuitable images without performing complete image recognition algorithms on all captured images
2Illumination intensity
If supplemental light is used to improve image brightness, then the visibility of license plate is improved, but the background noise increases
Solution Approach 1:
The system dynamically adjusts the image selection strategy based on lighting conditions by comparing brightness between images captured with and without supplemental light. This dynamic approach allows the system to adapt to varying environmental lighting conditions and select the most appropriate image for recognition, balancing brightness improvement against noise introduction
Solution Approach 2:
The system uses feedback from brightness comparison results to determine whether to proceed with image recognition. By analyzing the brightness difference between the first and second images, the system receives feedback on whether supplemental light appropriately enhanced the license plate visibility without excessive noise, and adjusts its processing accordingly
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces the number of images requiring processing and enhances the speed and accuracy of subsequent image recognition by effectively isolating the license plate image from background noise.
Implementation Method 1
a light compensating unit (120) emits supplemental light
Data Source
AI summary
A method for filtering driving images includes enabling a light compensating unit at a first time point to emit supplemental light, capturing a first driving image under the supplemental light at the first time point by an image capturing unit, disabling the light compensating unit at a second time point, capturing a second driving image at the second time point by the image capturing unit, selecting the first driving image according to a first brightness difference between the first driving image and the second driving image and a predetermined threshold, and outputting the first driving image when the first brightness difference is greater than or equal to the predetermined threshold.