Vehicle Camera RGCB Imaging for Human and Machine Vision
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Solution Overview
Problem
Conventional vehicle camera systems require separate cameras for human and machine vision, leading to duplication and increased costs.
Innovation Solution
A single vehicle camera system utilizing a red/green/clear/blue (RGCB) color filter array (CFA) and two different interpretation techniques to generate both human and machine vision images, leveraging the clear value as a luminance value for improved transmittance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If separate cameras are used for human and machine vision, then image quality for each specific application is optimized, but system cost and complexity increase
Solution Approach 1:
The patent applies universality by designing a single camera system that serves both human vision and machine vision functions. The camera uses an RGCB color filter array that captures both full-color information for human display and luminance-optimized data for machine processing, eliminating the need for separate dedicated cameras while maintaining functionality for both applications
Solution Approach 2:
The patent merges human vision and machine vision capabilities into a single imaging system. By combining the RGCB CFA optical path with dual processing modes (human vision processing and machine vision processing), the system consolidates what would traditionally require separate camera hardware into one unified device, reducing overall system complexity
2Reliability
If separate cameras are used for human and machine vision, then each camera can be optimized for its specific purpose, but manufacturing cost increases
Solution Approach 1:
The camera system achieves universality by incorporating an RGCB color filter array that simultaneously supports both human vision display requirements and machine vision processing needs. This single optimized component replaces what would traditionally require two separate camera systems, thereby reducing manufacturing costs while maintaining application-specific optimization
Solution Approach 2:
The patent applies parameter changes by modifying the traditional color filter array from standard RGB or RGGB configurations to an RGCB configuration. This parameter change in the optical filter design enables the single camera to capture data suitable for both human perception (color accuracy) and machine processing (luminance transmittance), achieving cost-effective multi-purpose optimization
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
Reduces vehicle costs and complexity by enabling a single camera to provide high-quality human and machine vision images for various applications, including autonomous driving features.
Implementation Method 1
an image sensor defining an array of photovoltaic cells each configured to detect light
Implementation Method 2
a red/green/clear/blue (RGCB) color filter array (CFA) configured to color filter the unfiltered array of light samples
Data Source
AI summary
A vehicle camera system configured for both human vision and machine vision functionality includes an image sensor defining an array of photovoltaic cells each configured to detect light and output an unfiltered array of light samples, a red/green/clear/blue (RGCB) color filter array (CFA) configured to color filter the unfiltered array of light samples and output an array of color samples, and a control system configured to apply a first interpretation technique to the array of color samples to obtain a human vision image and apply a different second interpretation technique to the array of color samples to obtain a machine vision image having a reduced color space and improved transmittance compared to the human vision image, wherein the second interpretation technique involves utilizing each clear value as a luminance value in the determination of red/green/blue values for each color sample.