Adaptive Color Filter for Digital Sensor
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Solution Overview
Problem
Conventional color filters used in photofinish cameras, such as the Bayer filter, suffer from reduced sensitivity due to light attenuation, and are not suitable for providing adequate image quality under varying racing conditions and weather conditions.
Innovation Solution
A parameterization method for an adaptive color filter comprising alternating columns of color pixels and white pixels, allowing for software-adjustable optical properties without physical movement of the camera, optimizing sensitivity and color quality based on predefined patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If a conventional color filter (e.g., Bayer filter) is used, then color image quality is achieved, but sensor sensitivity is reduced due to light attenuation
Solution Approach 1:
The sensor is divided into two distinct types of pixels: color pixels with specific color filters (RGB) and white pixels without color filters. This segmentation allows different regions to serve different functions - color pixels provide chromatic information while white pixels maximize light capture, resolving the contradiction between color quality and sensitivity
Solution Approach 2:
Different regions of the sensor have different optical properties. Color pixels use traditional color filters for accurate color reproduction, while white pixels use no filter or a broadband filter for maximum sensitivity. This local differentiation allows each pixel type to be optimized for its specific function
2Adaptability or versatility
If a fixed color filter pattern is used, then manufacturing simplicity is maintained, but adaptability to varying racing conditions and weather is reduced
Solution Approach 1:
The filter configuration is made dynamically adjustable through software control. The system can switch between different filter patterns (e.g., varying ratios of color to white pixels, different color filter combinations) based on detected racing conditions, ambient light levels, and weather, providing adaptability without mechanical complexity
Solution Approach 2:
The optical parameters of the filter system are made changeable through software. By adjusting which pixels are assigned to which filter types and configuring the filter characteristics, the system adapts to different racing speeds, lighting conditions, and weather scenarios without physical reconfiguration
3Productivity
If software adjustment is used instead of physical camera movement, then adjustment speed is improved, but operational complexity increases
Solution Approach 1:
The mechanical system of physically moving the camera or filter components is replaced with a software-based control system. Software algorithms dynamically adjust the effective filter configuration by selecting and combining signals from different pixel types, achieving rapid adaptation without mechanical movement or complex physical adjustments
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 method enables permanent optimization of optical properties for color photos, simplifies adjustment operations, and adapts to various racing conditions by adjusting sensitivity and resolution through software, ensuring high-quality image capture regardless of ambient light or racing speed.
Implementation Method 1
photosensitive sensors formed of a mosaic of pixels have been known for a long time; the sensors most commonly used for digital cameras use, for example, CCD (acronym for charge-coupled device) or CMOS (acronym for complementary metal oxide semiconductor) technology
Data Source
Figure 1
Figure 2~3
AI summary
Adjustment method for a photo-finish camera (3) comprising a matrix color filter, characterized in that it comprises the following steps: - a first step (E1) of choosing a basic pattern having predefined optical properties of sensitivity (S), color quality (Q) and resolution (N) according to race parameters; - a second step (E2) of software selection of a set of adjacent columns whose number corresponds to the width of said chosen basic pattern; - a third step (E3) of centering said set of adjacent columns on the finish line (2).