Mobile Camera Color Fastness Measurement With Pixel-Wise Analysis
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Solution Overview
Problem
Existing photometric camera systems for measuring color fastness are expensive and require specialized calibration, while less expensive cameras like those in smartphones are unsuitable for accurate color fastness measurements.
Innovation Solution
A portable computing device with a conventional camera is used to acquire digital images, calculating pixel-wise color fastness values by comparing individual pixels in a fabric sample to a reference region, employing various criteria to select an accurate color fastness value, and optionally using histogram analysis to filter noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If specialized photometric camera systems are used for measuring color fastness, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses a conventional camera to capture images of color fastness test samples, replacing the need for specialized photometric camera systems. The computational system processes these standard digital images to extract color information and calculate color fastness values, effectively copying the measurement function using ordinary equipment rather than dedicated instruments.
Solution Approach 2:
The patent replaces the mechanical/optical calibration systems traditionally required with computational image processing. Instead of using specialized photometric cameras with complex calibration mechanisms, the system uses standard cameras and applies computational algorithms to correct and analyze color data, substituting physical calibration infrastructure with software-based solutions.
2Device complexity
If conventional cameras are used for color fastness measurements, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent transforms the color image data from conventional cameras into accurate color fastness measurements by applying computational processing. The system extracts color values from image pixels, compares them against reference colors, and calculates color differences using standardized formulas, effectively changing the parameters from raw pixel values to meaningful color fastness metrics that compensate for the camera's limitations.
Solution Approach 2:
The patent introduces a computational system as an intermediary between the conventional camera and the color fastness measurement. This computational layer processes the raw image data, applies color space transformations, performs reference comparisons, and generates accurate color fastness values, acting as a mediator that bridges the gap between simple camera hardware and precise measurement requirements.
3Measurement precision
If expensive calibration systems are used, then measurement precision is improved, but loss of substance and cost increase
Solution Approach 1:
The patent enables the measurement system to self-calibrate using digital reference color values stored in the computational system. Instead of requiring physical calibration materials and complex calibration procedures, the system uses pre-defined reference colors in the color space to automatically correct and validate measurements, making the system self-sufficient and eliminating the need for external calibration infrastructure.
Data Source
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AI summary
Disclosed herein is a portable computing device (100) comprising a camera. The execution of machine executable instructions (119) causes a computational system to (102): control (300) the camera to acquire a digital image 120); identify (302) a reference region (122) within the digital image; identify (304) a sample region (124) within the digital image; identify (306) a color reference region (126) in the digital image; receive (308) a reference color distance (136) for each of multiple color fastness values (140); calculate (310) a pixel wise sample color distance (134) between pixels in the sample region and the reference region; calculate (314) a pixel wise color fastness value (138) of the individual pixels in the sample region; and select (316) a color fastness value (140) for the sample region using the pixel wise color fastness value.