Image-Based Color Palette Extraction for Faster Content Editing
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Solution Overview
Problem
Existing contents editing applications face usability challenges in selecting and matching colors, particularly when users aim to replicate the colors of actual items, as conventional color palettes are limited and finding desired colors is time-consuming and difficult.
Innovation Solution
A contents editing application that automatically extracts specific colors from image data and displays a color palette with a color object indicating these colors, allowing users to easily change the color of editing targets based on their selection in the palette.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional color palettes are used in contents editing applications, then the application structure remains simple, but users experience difficulty in finding and selecting desired colors, reducing usability
Solution Approach 1:
The system performs preliminary color extraction from reference images before the user needs to select colors. By automatically analyzing the image data and extracting characteristic colors in advance, the color palette is pre-populated with relevant colors, eliminating the time users would otherwise spend searching for appropriate colors manually.
Solution Approach 2:
The system enables self-service color selection by automatically generating a customized color palette based on the uploaded reference image. The application autonomously analyzes the image, extracts dominant and characteristic colors, and presents them in an organized palette, allowing users to select colors without manual searching or complex operations.
2Adaptability or versatility
If all colors from image data are included in the color palette, then color selection completeness is improved, but the palette becomes too large and overwhelming for users
Solution Approach 1:
The system extracts only the most relevant colors from the comprehensive set of colors in the image data. By identifying and separating the dominant colors and characteristic colors that best represent the image, the system presents a curated subset in the color palette, maintaining completeness of color representation while reducing the number of options to a manageable level.
Solution Approach 2:
The system applies different selection criteria to different portions of the color spectrum in the image data. Rather than treating all colors equally, it identifies specific regions of interest in the color space (dominant colors and characteristic colors) and extracts colors from these specific regions, creating a palette that is both comprehensive in representation and concise in size.
3Measurement precision
If automatic color extraction is implemented, then color matching accuracy is improved, but the processing complexity and computational requirements increase
Solution Approach 1:
The system performs color extraction as a preliminary processing step before the main editing workflow. By completing the computationally intensive image analysis and color identification in advance, the system stores the extracted color data for quick retrieval during editing, maintaining high color matching accuracy while reducing real-time processing requirements.
Data Source
AI summary
A non-transitory computer readable storage medium storing a program which causes a computer to execute: obtaining image data; and displaying, on a basis of that a specific color included in the obtained image data is automatically extracted, a first color palette including a color object indicating the specific color, the specific color being at least one, but not all, of colors of a plurality of colors included in the obtained image data, wherein the displaying includes changing a color of editing target contents to the specific color on a basis of that the color object indicating the specific color is selected in the first color palette.