Vehicular Image Pickup Device Dynamic Exposure Control
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Solution Overview
Problem
Conventional image pickup devices mounted on moving objects, such as vehicles, experience deteriorated image quality due to speed, affecting the accuracy of image recognition.
Innovation Solution
A vehicular image pickup device comprising an image capturing unit, a fill light unit, and a processing unit that adjusts fill light intensity or gain based on grayscale quantity distribution to maintain appropriate brightness, and fine-tunes shutter speed and fill light intensity according to frequency spectrum and brightness distribution for enhanced image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a conventional image pickup device is mounted on a moving vehicle, then the image pickup device can capture images from moving positions, but the image quality deteriorates due to vehicle speed
Solution Approach 1:
The patent implements dynamic adjustment of exposure parameters (shutter speed, gain, fill light intensity) based on real-time vehicle speed and lighting conditions. The processing unit continuously monitors image quality metrics and adjusts capture parameters to compensate for motion-induced degradation, transforming a static capture system into an adaptive dynamic one that maintains image quality despite vehicle movement
Solution Approach 2:
The system changes multiple capture parameters simultaneously - shutter speed is adjusted to prevent motion blur, gain is modified to maintain exposure levels, and fill light intensity is varied to compensate for changing lighting conditions. These parameter changes are coordinated based on vehicle speed and ambient light levels to maintain optimal image quality during mobile operation
2Manufacturing precision
If the image pickup device adjusts exposure parameters in real-time, then image quality is maintained, but the processing complexity increases
Solution Approach 1:
The processing unit implements a feedback mechanism that analyzes captured images for quality metrics (exposure level, motion blur detection) and uses this information to adjust subsequent capture parameters. This closed-loop control system automatically compensates for degradation without requiring complex manual intervention, balancing image quality maintenance with manageable processing complexity
Solution Approach 2:
The system performs self-adjustment of exposure parameters by automatically analyzing image quality metrics and modifying capture settings without external intervention. The processing unit monitors image characteristics and autonomously adjusts shutter speed, gain, and fill light to maintain optimal quality, reducing the need for complex external control systems
3Ease of operation
If conventional image pickup devices operate with fixed parameters, then the device operation is simple, but image quality varies with lighting conditions and speed
Solution Approach 1:
The system transitions from static fixed parameters to dynamic adaptive parameters that automatically adjust to changing conditions. The processing unit continuously modifies exposure settings based on real-time vehicle speed and lighting environment, maintaining operational simplicity while achieving consistent image quality across varying conditions through automated parameter adaptation
Data Source
AI summary
A vehicular image pickup device includes an image capturing unit, a fill light unit and a processing unit. The image capturing unit captures driving images. The fill light unit provides a fill light. The processing unit obtains a grayscale quantity distribution of pixels of the driving images on a plurality of grayscale levels. The processing unit numbers the pixels sequentially in the direction from the highest grayscale level to the lowest grayscale level according to the grayscale quantity distribution until the numbering reaches a predetermined number. The processing unit adjusts a fill light intensity of the fill light unit or a gain of the image capturing unit according to the grayscale level of the pixel whose number is the predetermined number.