Driver Monitoring Pupil Detection Light Intensity Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional driver monitoring systems face challenges in efficiently adjusting light intensity based on ambient light levels, leading to increased power consumption and potential inaccuracies in determining the driver's state, especially under varying lighting conditions.
Innovation Solution
The system incorporates an image processing apparatus that uses an illumination apparatus and imaging apparatus to capture images of the driver's pupil, determining the ambient light level by analyzing brightness patterns and adjusting the light intensity accordingly, thereby reducing power consumption and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If light intensity is increased to improve image capture quality, then measurement precision is improved, but power consumption increases
Solution Approach 1:
The light intensity is made dynamically adjustable based on ambient light conditions. The system switches between high intensity (when ambient light is low) and low intensity (when ambient light is high), optimizing both measurement precision and power consumption according to real-time conditions
Solution Approach 2:
The system changes the light intensity parameter based on ambient light level detection. By adjusting this physical parameter according to environmental conditions, the system achieves accurate pupil measurement while minimizing unnecessary power consumption
2Measurement precision
If light intensity is increased to ensure accurate driver state monitoring, then measurement precision is improved, but harmful factors increase
Solution Approach 1:
The illumination intensity is dynamically adapted to ambient conditions, providing high intensity only when necessary (low ambient light) and reducing intensity when ambient light is sufficient, thereby minimizing eye burden while maintaining detection accuracy
Solution Approach 2:
The system uses ambient light conditions to its advantage, leveraging natural light availability to reduce the need for artificial illumination, thereby protecting the driver's eyes while maintaining monitoring effectiveness
3Measurement precision
If fixed high light intensity is used for all conditions, then measurement precision is maintained, but power consumption increases
Solution Approach 1:
The system changes the light intensity parameter based on ambient light level detection, switching between high and low intensity modes to match environmental conditions, thereby eliminating energy waste while preserving measurement accuracy when needed
Solution Approach 2:
The system incorporates feedback from ambient light detection to control light intensity output, creating a closed-loop system that adjusts illumination based on actual conditions, preventing energy waste while maintaining measurement precision
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 allows for dynamic adjustment of light intensity based on the driver's pupil size, reducing power consumption, extending the life of the light source, and enhancing the system's ability to accurately determine the driver's state by minimizing the burden on the driver's eyes and reducing noise from high ambient light.
Implementation Method 1
an imaging apparatus 12 configured to capture an image of the pupil illuminated by the light
Data Source
Figure 1
Figure 2~3
Figure 4A~5B
AI summary
An image processing apparatus 13 includes an image acquiring unit 29 and a controller 31. The image acquiring unit 29 acquires a captured image capturing a subject 18 illuminated by light from at least one light source 19. The controller 31 generates adjustment information for adjusting an intensity of the light from the at least one light source 19 on the basis of a size of a pupil of the subject 18 determined from the captured image.