Camera Calibration for Analyte Detection Using Color Space Transformation
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Solution Overview
Problem
Existing camera calibration methods for detecting analytes in samples, particularly using consumer electronics like smartphones, face challenges in accurately determining analyte concentrations due to non-linear factors such as varying lighting conditions and individual technical and optical properties of cameras, which can lead to measurement inaccuracies.
Innovation Solution
A calibration method that involves providing a set of color coordinate systems, test samples with known analyte concentrations, and test elements with optically detectable detection reactions, acquiring images, generating color coordinates, and using coding functions to transform these coordinates into measured concentrations, while comparing and determining the best match color coordinate system and coding function to achieve accurate calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a camera from consumer electronics is used for detecting analytes, then device availability and ease of operation are improved, but measurement precision deteriorates due to non-linear factors like varying lighting conditions and individual camera properties
Solution Approach 1:
The patent applies parameter changes by transforming color coordinates from the camera's native color space to a standardized color space (such as CIE 1931 XYZ or CIE 1976 L*a*b*). This transformation adjusts the color parameters to compensate for camera-specific non-linearities and lighting conditions, enabling accurate analyte concentration measurements while maintaining ease of use with consumer cameras
Solution Approach 2:
The patent introduces color coordinate transformations as an intermediary step between the camera's raw color data and the final analyte concentration calculation. This intermediary transformation layer mediates the relationship between the camera's inherent non-linearities and the requirements for precise measurement, allowing consumer cameras to achieve laboratory-grade accuracy
2Measurement precision
If calibration is performed under predefined conditions, then measurement precision is improved, but adaptability deteriorates because the system cannot handle varying lighting and environmental conditions
Solution Approach 1:
The patent performs preliminary action by establishing a calibration curve during an initial calibration phase under controlled conditions. This calibration curve serves as a reference that can be applied to subsequent measurements under varying conditions, enabling the system to maintain precision without requiring repeated calibration under identical conditions
Solution Approach 2:
The patent uses parameter changes through color space transformation to adapt the calibration results to different lighting and environmental conditions. By transforming color coordinates to a standardized space, the system can maintain measurement precision across varying conditions without sacrificing adaptability
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 enhances measurement accuracy and convenience by accounting for non-linear factors and optimizing color representation, leading to improved determination of analyte concentrations in samples.
Implementation Method 1
test elements, each test element having at least one test field comprising at least one test chemical configured for performing an optically detectable detection reaction with the analyte
Implementation Method 2
acquiring images of the colored test fields by using the camera
Data Source
AI summary
A calibration method for calibrating a camera for detecting an analyte in a sample is disclosed. A plurality of different color coordinate systems and a set of test samples are provided. The test samples are applied to test elements that have test fields for producing an optically detectable reaction. Images of the colored test fields are acquired using the camera and color coordinates for the images are generated. The color coordinates that are generated are transformed into a set of measured concentrations by using a set of coding functions. The set of measured concentrations is compared with the known concentrations of the test samples and a best match color coordinate system of the plurality of color coordinate systems is determined. A best match coding function of the plurality of coding functions is also determined.