Vehicle Display Image Enhancement for Nighttime Object Detection
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Solution Overview
Problem
Current vehicle camera and display systems are inadequate in low-light conditions, such as nighttime driving, leading to reduced object detection and identification performance, and the use of night-vision camera systems increases weight and system complexity.
Innovation Solution
A system utilizing a machine learning algorithm trained with a dataset of image pairs to enhance nighttime images, enabling object identification and notification using augmented reality head-up displays or transparent windscreen displays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If night-vision camera systems are used to provide perception capability in low-light conditions, then illumination intensity is improved, but device complexity and weight increase
Solution Approach 1:
The patent changes the operational parameters of the existing color camera system by adjusting exposure time and applying machine learning-based image enhancement algorithms. This allows the camera to capture and process nighttime images using visible light parameters rather than requiring infrared or thermal sensors, thereby improving low-light perception without increasing device complexity
Solution Approach 2:
The patent creates an enhanced version of the nighttime image through machine learning algorithms that simulate what the scene would look like under better lighting conditions. This digital copying and enhancement approach replaces the need for physical night-vision hardware, reducing system complexity while maintaining perception capability
2Illumination intensity
If night-vision camera systems are used to provide perception capability in low-light conditions, then illumination intensity is improved, but weight increases
Solution Approach 1:
The patent modifies the operational parameters of the existing color camera to enable nighttime operation by extending exposure time and applying computational enhancement, eliminating the need for additional night-vision camera hardware and associated weight
Solution Approach 2:
The patent makes the existing color camera system multi-functional by enabling it to operate effectively in both daytime and nighttime conditions through parameter adjustment and algorithmic enhancement, replacing the need for separate night-vision camera systems
3Device complexity
If existing color camera systems are used in nighttime conditions, then device complexity is maintained, but measurement precision deteriorates
Solution Approach 1:
The patent introduces machine learning algorithms as an intermediary processing layer between the color camera sensor and the object detection system. This intermediary enhances the quality of nighttime images by reducing noise and improving contrast, thereby restoring measurement precision without complicating the hardware system
Solution Approach 2:
The patent replaces hardware-based image enhancement mechanisms with software-based machine learning algorithms. This substitution maintains simple hardware architecture while achieving high measurement precision through computational methods that enhance nighttime image quality
Data Source
AI summary
A method for providing information to an occupant of a vehicle includes training a machine learning algorithm to receive a nighttime image as an input and produce an enhanced image as an output. The method also includes capturing the nighttime image of an environment surrounding the vehicle using a camera of the vehicle. The method also includes enhancing the nighttime image using the machine learning algorithm to produce the enhanced image. The method also includes identifying an object of interest in the enhanced image using a computer vision algorithm. The method also includes notifying the occupant of the vehicle about the object of interest.