Digital Camera Control System for License Plate Imaging
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Solution Overview
Problem
High-speed digital cameras used in traffic law enforcement struggle to capture legible images of license plates under varying lighting conditions, requiring dynamic gain adjustments that are often delayed or inaccurate due to reliance on external sensors or pixel value measurements, leading to image saturation and poor contrast.
Innovation Solution
A control system that uses environmental and illumination models to predict and set optimized camera settings based on geographic location, time, and weather conditions, eliminating the need for external sensors and allowing for pre-emptive adjustment of exposure parameters to ensure sufficient contrast and prevent saturation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If the camera gain is increased to improve contrast in low light conditions, then the contrast for character recognition is improved, but the image sensor saturates in high light conditions
Solution Approach 1:
The control system calculates exposure settings in advance based on predicted lighting conditions (sun position, shadow patterns, time of day) before the vehicle enters the field of view. This preliminary calculation allows the system to pre-configure the camera gain and exposure time to match upcoming lighting scenarios, preventing both saturation and insufficient contrast
Solution Approach 2:
The system dynamically adjusts camera exposure settings (gain and exposure time) based on real-time lighting conditions and predicted changes. The control system continuously monitors environmental factors and modifies exposure parameters adaptively, transitioning between high gain for shadowed areas and low gain for sunlit areas during the exposure period
2Measurement precision
If external sensors are used to measure lighting conditions for gain control, then the accuracy of exposure settings is improved, but the system complexity and cost increase
Solution Approach 1:
The camera system uses its own pixel array to measure lighting conditions and calculate exposure settings, eliminating the need for external sensors. The control system processes the digital video signal from the camera's sensor to determine optimal exposure parameters, making the system self-sufficient and reducing external dependencies
Solution Approach 2:
The camera's pixel array serves dual functions: capturing the actual image data and simultaneously measuring lighting conditions for exposure control. This multi-functionality eliminates the need for separate external sensors while maintaining measurement accuracy
3Speed
If the camera adjusts gain settings during the time the vehicle is in the field of view, then the response time is reduced, but the image quality deteriorates due to motion blur and timing delays
Solution Approach 1:
The control system calculates and sets exposure parameters before the vehicle enters the camera's field of view by using predicted lighting conditions based on time, date, location, and shadow analysis. This advance preparation ensures the camera is properly configured when the vehicle appears, avoiding motion blur and timing delays
Solution Approach 2:
The system continuously monitors the digital video signal from the camera sensor and uses this feedback to verify and adjust exposure settings. By analyzing the actual image data in real-time, the control system ensures optimal exposure is maintained throughout the vehicle passage
Data Source
AI summary
A digital camera control system that requires no light sensors is described. The control system relies on modeled external environmental geophysical solar parameters, geometric relationships between the object to be imaged and surrounding potentially shadowing objects, the material properties of the object to be imaged such as reflectivity are combined to produce the estimated irradiance on a camera sensor for the particular time of day, date and geometric relationship between the object and the sun. The calculated irradiance on the image sensor for the background of the object of interest and a feature to be recognized provide a contrast. The signal to noise requirements for the feature recognition are used to determine a minimum required contrast transfer function for the sensor. Control parameters for the sensor are then determined to meet the minimum contrast requirements. The system therefore provides a method to rapidly determine an optimum camera settings for any time of day and ensures the camera is always ready to capture at least the minimum required contrast image of a fast moving transient object. The system is demonstrated for use in a license plate imaging application.