HSV Color Correction Using Reference Cards
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Solution Overview
Problem
Existing image correction methods fail to accurately adjust for color distortion caused by varying light sources, particularly in home office environments, leading to inaccurate color representation and hue changes in video conferencing and remote teaching.
Innovation Solution
A method using a color card with predefined color blocks to capture RGB values, convert them to HSV values, and automatically adjust HSV values based on predefined standards to correct for light source variations, ensuring accurate color representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automatic white balance function is used to adjust color temperature, then color adjustment is applied to the entire image, but this creates color filter effect and changes overall hue, leading to inaccurate color representation
Solution Approach 1:
The patent applies local quality by selectively adjusting only the color blocks that deviate from their reference colors, rather than applying uniform white balance adjustment to the entire image. The processing module identifies specific color blocks needing correction and adjusts their saturation and hue independently, preserving the natural appearance of skin tones and other image regions while correcting only the distorted color blocks.
Solution Approach 2:
The patent changes parameters by adjusting saturation and hue of specific color blocks based on their deviation from reference colors, rather than applying global white balance parameters. The system calculates the difference between captured color block values and reference values, then applies targeted parameter adjustments to correct color distortion without affecting the overall image hue.
2Ease of operation
If commercially available color cards are used for color correction, then color calibration is attempted, but end-users cannot perform calibration themselves and optimal display effect is not achieved under multiple light sources
Solution Approach 1:
The patent implements self-service by enabling end-users to perform color calibration independently through an automated process. Users simply capture an image containing the color card, and the system automatically identifies color blocks, compares them against reference values, and applies corrections without requiring user expertise in color theory or manual adjustment. This makes professional-grade color calibration accessible to ordinary users.
Solution Approach 2:
The patent applies preliminary action by pre-storing reference color values for each color block in a database before the calibration process. These reference values are captured under controlled lighting conditions and used as the basis for comparison during user calibration. This preliminary preparation enables accurate correction by providing a known standard against which to measure and correct color deviations.
3Manufacturing precision
If commercially available color cards are used for color correction, then color calibration is performed, but accuracy of skin tones under different light sources still has room for improvement
Solution Approach 1:
The patent applies dynamics by adaptively adjusting saturation and hue parameters based on the specific lighting conditions detected in each scene. Rather than applying fixed correction values, the system dynamically calculates the necessary adjustments by comparing captured color blocks against reference values and modifying parameters in real-time according to the actual lighting environment, thereby improving skin tone accuracy across diverse light sources.
Solution Approach 2:
The patent changes parameters by selectively adjusting saturation and hue of color blocks based on their deviation from reference colors, with special consideration for skin tone regions. The system modifies these parameters dynamically according to detected lighting conditions, enabling accurate skin tone representation under various light sources while maintaining natural appearance.
Data Source
AI summary
An image correction method includes the following steps: (1) obtaining a color card including color blocks, where each of the color blocks has a predefined color standard; (2) placing an image capturing device and the color card in a selected operating environment; (3) using a system of the image capturing device to capture RGB values of each of the color blocks on the color card and converting the RGB values into HSV values; (4) comparing the predefined color standard of each of the color blocks with the HSV values of each of the color blocks to determine a degree of difference in H value, S value and V value between the predefined color standards and the HSV values; and (5) automatically adjusting the HSV values according to the predefined color standards and the degree of difference of each of the color blocks.