Search Result Image Selection by Color Similarity
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Solution Overview
Problem
Existing search engines fail to accurately select and rank products or services based on color characteristics specified in search queries, often displaying irrelevant results.
Innovation Solution
A system and method that analyze search queries for color references, determine the user's intent regarding colors, and modify search result rankings by increasing the visibility of products with matching or similar colors, using color analysis modules and similarity scoring to enhance relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing search engines display search results without color-based filtering, then the search process is simple and fast, but the accuracy and relevance of search results deteriorate
Solution Approach 1:
The patent segments the search process into distinct modules: a color analysis module that extracts color information from product images, a color matching module that compares query colors with product colors, and a ranking module that reorders results based on color similarity. This segmentation allows the system to add color-based filtering without completely redesigning the search engine architecture.
Solution Approach 2:
The patent introduces color metadata as an intermediary layer between the user's color query and the product database. Color profiles are extracted from product images and stored as intermediate data structures, enabling efficient color-based filtering without requiring complex real-time image analysis during the search process.
2Measurement precision
If search engines analyze color characteristics of all products, then color-based search accuracy improves, but the processing time and computational resources increase
Solution Approach 1:
The patent performs color analysis as a preliminary action during product listing or catalog generation, rather than during the actual search process. Color profiles are pre-computed and stored with product metadata, so when a user performs a color-based search, the system only needs to query and compare pre-analyzed color data, significantly reducing processing time.
Solution Approach 2:
The patent transforms color information from complex image data into simplified numerical parameters (color profiles, color histograms, or standardized color space values). This parameter transformation enables efficient computational comparison and filtering while maintaining color matching accuracy.
3Ease of operation
If search engines ignore color characteristics, then the search system remains simple, but the user satisfaction and result relevance deteriorate
Solution Approach 1:
The patent designs the color analysis module to work universally across different product types and image formats. The same color extraction and matching algorithms are applied regardless of product category, enabling the system to handle diverse search queries with a single unified approach while maintaining simplicity.
Solution Approach 2:
The patent implements automatic color profile extraction from product images without requiring manual input from users or sellers. The system autonomously analyzes images, extracts color characteristics, and integrates this information into the search index, eliminating the need for complex user interfaces or manual data entry while improving result relevance.
Data Source
AI summary
Example systems and methods that select search result images are described. In one implementation, a method accesses a ranking of multiple products associated with a search query and identifies a reference to a color in the search query. The method identifies a first product from the ranking of multiple products and identifies multiple product images associated with the first product. A color determination is made regarding each of the multiple product images. A product image having an associated color that is most similar to the color in the search query is selected for presentation in the search results.