Automated Color Palette Generation for E-Commerce
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Solution Overview
Problem
Current computing-centric commerce models lack efficient methods for extracting and utilizing representative colors from color images to facilitate color-matching item sales, as existing technologies do not effectively generate and utilize color palettes based on user preferences and metadata.
Innovation Solution
An image processing service that generates color palettes by pre-processing color images, identifying representative colors through color distribution and distance formulas, and associating them with metadata, allowing for user input or automatic optimization based on popularity and other criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual color extraction methods are used, then color accuracy is maintained, but processing efficiency and productivity are poor
Solution Approach 1:
The patent replaces manual mechanical color extraction processes with automated image processing algorithms and computer vision techniques. The system uses digital image analysis, color space transformations, and automated palette generation algorithms to extract representative colors from product images, eliminating the need for manual color picking while maintaining or improving accuracy through consistent computational methods.
Solution Approach 2:
The system enables automated self-service color extraction where the image processing service automatically analyzes product images, identifies dominant colors, generates color palettes, and associates them with product metadata without human intervention. This self-automating process handles large volumes of images efficiently while maintaining color accuracy through standardized processing pipelines.
2Measurement precision
If comprehensive color analysis is performed, then color matching accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the color analysis process into distinct modular stages: image pre-processing, color space conversion, dominant color identification, palette generation, and metadata association. Each stage handles a specific aspect of color analysis independently, reducing overall computational complexity while maintaining comprehensive analysis through systematic breakdown of the problem into manageable components.
Solution Approach 2:
The system implements partial color analysis by focusing on extracting only the most dominant and representative colors from product images rather than analyzing every pixel exhaustively. The automated palette generation identifies key color themes and representative hues that capture the essential color information, providing sufficient accuracy for commerce applications without requiring complete exhaustive analysis of all color data.
3Productivity
If automated palette generation is implemented, then productivity increases, but control over color selection and customization decreases
Solution Approach 1:
The patent implements a dynamic color palette generation system that can adapt between fully automated operation and user-guided customization. The system allows users to input preferences, specify color constraints, or adjust parameters interactively while the automated processing engine handles the computational workload. This dynamic flexibility enables users to maintain control over color selection criteria while benefiting from automated efficiency in executing the color extraction and palette generation processes.
Data Source
AI summary
Systems and methods are provided for generating an image-based color palette based on a color image. A color palette can be a collection of representative colors each associated with a weight or other metadata. A color palette may be generated based on palette generation criteria, which may facilitate or control a palette generation process. Illustratively, the palette generation process may include image pre-processing, color distribution generation, representative color identification, palette candidate generation and palette determination. Representative colors with associated weight can be identified from a distribution of colors depicted by the color image, multiple palette candidates corresponding to the same color image can be generated based on various palette generation criteria, and a color palette can be identified therefrom.