Adaptive Camera Exposure Control for Robust Image Recognition
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Solution Overview
Problem
Image recognition systems in mobile bodies face challenges in maintaining accuracy due to varying environmental conditions and disturbances, as they often rely on assumptions of consistent image-capturing conditions that are not met in real-world scenarios, leading to degraded recognition performance.
Innovation Solution
An image recognition system that includes an image acquisition unit, a recognition model generation unit, and a state estimation unit to optimize imaging device conditions by estimating the state and characteristics of the imaging device, generating correction parameters for shutter open time, aperture open degree, and image signal processing to adapt to changing environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image conversion is performed to match learning conditions, then recognition accuracy is improved under assumed conditions, but recognition accuracy deteriorates when image information is already degraded or missing
Solution Approach 1:
The patent applies dynamics by making the image-capturing conditions adjustable and adaptable rather than fixed. The system dynamically adjusts imaging parameters such as illumination intensity, shutter speed, and aperture based on real-time environmental feedback, allowing the imaging device to optimize capture conditions for each specific situation rather than relying on predetermined conversion processes
Solution Approach 2:
The patent applies preliminary action by pre-adjusting image-capturing conditions before image acquisition occurs. The system proactively optimizes illumination, exposure, and focus settings based on predicted environmental conditions, ensuring that images are captured under optimal conditions from the outset rather than attempting to correct degraded information afterward
2Measurement precision
If image-capturing conditions are adjusted to adapt to environment, then recognition accuracy is improved, but device complexity increases
Solution Approach 1:
The patent applies feedback by implementing a closed-loop system where environmental conditions are continuously monitored and used to adjust image-capturing parameters. Sensors detect illumination levels, contrast, and other environmental factors, and this information feeds back to automatically adjust camera settings, eliminating the need for complex manual conversion processes while maintaining high recognition accuracy
Solution Approach 2:
The patent applies self-service by enabling the imaging system to automatically adjust its own capture conditions without external intervention. The system autonomously monitors environmental changes and modifies illumination, exposure, and other parameters independently, reducing the need for complex external control mechanisms
Data Source
AI summary
The present invention optimizes conditions of an imaging device when acquiring an image so as to improve the accuracy of image recognition. An image recognition system comprises: an image acquisition unit for acquiring an image captured by an imaging device; a recognition model generation unit having at least one environment recognition unit, recognizing at least one image by the environment recognition unit, and generating a recognition model; and a state estimation unit for estimating the state of the imaging device and the characteristic of the imaging device that corresponds to said state, on the basis of the image and the recognition model. The state estimation unit further generates an imaging correction parameter to correct the imaging condition of the imaging device, on the basis of the estimated state and characteristic and/or the recognition model.