Image Processing Engine Component Generation for Search Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image search technologies rely on descriptive text information, which often fails to accurately represent image content, leading to significant differences between searched and needed images, resulting in poor user experiences.
Innovation Solution
An image processing engine component generation method and system that determines and adds image content feature information, such as labels and feature vectors, to index tables, enabling more accurate searches by correlating search text information with actual image content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image search relies on descriptive text information, then the search process is simple, but the search accuracy deteriorates
Solution Approach 1:
The patent introduces image content feature information as an intermediary between the image and search text information. This intermediary consists of image content feature extraction (converting image to feature vectors) and image content feature matching (matching features with search queries), which bridges the gap between simple text search and accurate image content representation, thereby improving search accuracy without requiring complete system redesign
Solution Approach 2:
The patent replaces the traditional text-based search mechanism with an image content feature-based mechanism. Instead of relying on descriptive text information, the system extracts visual features from images (such as color, shape, texture) and uses these features for search matching, substituting the mechanical text-processing system with an automated image-feature processing system that achieves higher accuracy
2Reliability
If descriptive text information is used for image search, then the implementation is straightforward, but the correlation between search results and needed images deteriorates
Solution Approach 1:
The patent extracts essential image content features from the full image data. By extracting key visual characteristics (color distribution, shape contours, texture patterns) and representing them as compact feature vectors, the system captures the most important image information for search purposes, reducing information loss while maintaining search result relevance
Solution Approach 2:
The patent performs preliminary image content feature extraction and indexing before actual search operations. Image features are pre-computed and stored in an index structure, enabling rapid matching during search. This preliminary action ensures that when search occurs, the system already has processed and organized image content information, preventing information loss and improving search reliability
Data Source
AI summary
An image processing engine component generation method, and search method, terminal, and system are provided. The image processing engine component includes: an online feature processing component operative to receive an incremental image, and determine image content feature information of the incremental image; an offline feature processing component operative to receive a stock image, and determine image content feature information of the stock image; a search platform component operative to receive a search request, the search request including search text information; and a processing engine component operative to receive image content feature information of the incremental image and the stock image, add the received image content feature information to index tables, and determine search results corresponding to the search text information. Utilization of example embodiments of the present disclosure may ensure correlation between image content feature information designated as index information in the index tables and image content, thereby ensuring the accuracy of search results.