Spectrometry Apparatus Color Unevenness Quantification
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Solution Overview
Problem
Existing spectrometry apparatuses lack a color unevenness quantifying component, making it impossible to properly evaluate color unevenness, which is essential for automatic product visual inspection and replacing human sensory inspection.
Innovation Solution
A spectrometry method and apparatus that includes a spectrometer for spectral separation of reflected light, an imaging device for capturing spectroscopic images, and a controller for generating spectroscopic images, dividing the image into regions, calculating tristimulus values, and determining color differences using a color difference formula to quantify color unevenness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a spectrometry apparatus uses a spectrometer to capture spectroscopic images across multiple wavelength bands, then the ability to evaluate color properties is improved, but the apparatus still cannot properly evaluate color unevenness without additional processing components
Solution Approach 1:
The image processing function is segmented into distinct computational steps: dividing the spectroscopic image into multiple regions, calculating tristimulus values for each region, determining reference values, and computing color differences. This segmentation allows complex color unevenness evaluation to be achieved through software processing rather than adding complex hardware components.
Solution Approach 2:
Tristimulus values serve as an intermediary representation between the raw spectral data and the final color unevenness evaluation. By converting spectral information into tristimulus values and then into color space coordinates, the system creates intermediate representations that facilitate accurate color difference calculation without requiring direct complex hardware modifications.
2Measurement precision
If the spectrometry apparatus captures spectroscopic images without region-based analysis, then the imaging process is simplified, but color unevenness cannot be properly quantified
Solution Approach 1:
The spectroscopic image is divided into multiple regions to enable localized color analysis. By segmenting the image into distinct areas, the system can calculate tristimulus values and color coordinates for each region separately, making it possible to detect and quantify color unevenness that would be invisible in a whole-image average analysis.
Solution Approach 2:
The system performs analysis on multiple regions rather than the entire image as a single unit. This partial action approach allows focused evaluation of specific areas where color unevenness may occur, providing sufficient measurement precision without the excessive complexity of analyzing every pixel individually.
3Measurement precision
If the apparatus calculates color values without using tristimulus values and color difference formulas, then the processing is simpler, but accurate color unevenness evaluation is not achieved
Solution Approach 1:
The system performs preliminary calculation of tristimulus values from spectral data before computing color coordinates and color differences. This preliminary action prepares the data in a standardized format that facilitates accurate color space transformations and color difference calculations, ensuring measurement precision while maintaining processing efficiency through systematic data preparation.
Solution Approach 2:
The patent replaces direct spectral comparison with a standardized colorimetric approach using tristimulus values and color difference formulas. This substitution transforms complex spectral analysis into standardized color space calculations, achieving accurate color unevenness evaluation through well-established colorimetric theory rather than ad-hoc spectral processing.
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
Enables accurate quantification of color unevenness, allowing for the replacement of human inspection with automatic inspection in product visual evaluation by calculating color differences based on optical spectra across multiple wavelength bands, independent of illumination light effects.
Implementation Method 1
a spectrometry section including a spectrometer that spectrally separates reflected light reflected off an imaging target to select light having a predetermined wavelength
Data Source
AI summary
A spectrometry method used by a spectrometry apparatus including a spectrometry section including a spectrometer and an imaging device that captures a spectroscopic image, a spectroscopic controller that controls the action of the spectrometer, and an image generator that generates the spectroscopic image, the method including generating the spectroscopic image, dividing the range of the spectroscopic image into a plurality of regions including at least a first region, determining a reference value of a color value, generating a first region spectrum based on the spectroscopic image of the first region, calculating first region tristimulus values based on the first region spectrum, calculating a first region color value based on the first region tristimulus values, and calculating a first region color difference that is the color difference between the first region color value and the reference value by using a color difference formula.