Perceptual Color Matching for Image Region Selection
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Solution Overview
Problem
Current digital image editing tools face challenges in selectively editing specific portions of an image, particularly in isolating and modifying colors with shading variations, as they rely on manual tracing or simplistic color matching methods that do not account for perceptual color attributes or illumination principles.
Innovation Solution
A methodology that computes perceptual color differences between a reference color and pixel values in an image, allowing for the selection of image objects or regions by color, using chromaticity diagrams and tolerance settings to accurately capture shading variations, based on principles of color science and light interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracing methods (lasso tool) are used to select image regions, then selection accuracy can be achieved, but user time and effort are significantly increased
Solution Approach 1:
The patent replaces manual mechanical tracing operations with an automated color-based selection system. The magic wand tool automatically identifies and selects pixels based on color similarity to a reference point, eliminating the need for manual pixel-by-pixel tracing while maintaining selection accuracy through perceptual color matching algorithms.
Solution Approach 2:
The selection system performs self-service by automatically identifying and selecting regions based on color properties without requiring continuous user intervention. Once the user specifies a reference color point and tolerance level, the system autonomously computes and selects all matching pixels, including those with shading variations, without further manual input.
2Extent of automation
If simplistic color matching based on RGB values is used, then automation is improved, but color selection accuracy deteriorates due to inability to handle shading variations
Solution Approach 1:
The patent transforms the color matching approach by changing from direct RGB value comparison to perceptual color space comparison. By converting RGB values to perceptual color coordinates and using tolerance-based matching in this transformed space, the system automatically handles shading variations while maintaining color selection accuracy, as the perceptual space better represents human color perception.
3Adaptability or versatility
If tolerance settings are adjusted to capture shading variations, then color matching capability is improved, but selection precision deteriorates by including unwanted colors
Solution Approach 1:
The patent adds a perceptual dimension to color matching by operating in perceptual color space rather than raw RGB space. This dimensional transformation allows the tolerance setting to operate in a space that naturally accounts for human color perception, enabling the system to capture shading variations while excluding dissimilar colors that would be incorrectly included in raw RGB space.
Data Source
AI summary
A method or computer program product for color selection in a color image, including operations or instructions for selecting a base color in a base color portion of a color image; computing a perceptual color difference between the base color and a respective second color in the color image; comparing the perceptual color difference to a tolerance; and, identifying whether the color difference satisfies the tolerance.