Multi-dimensional Search System Using Image Pattern Recognition
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Solution Overview
Problem
Conventional search engines are text-centric and inefficient, requiring users to manually input keywords and Boolean operators to find relevant information, leading to a time-consuming and frustrating search process due to the reliance on pre-indexed metadata and manual tagging of visual attributes.
Innovation Solution
A multi-dimensional search system that analyzes inputs such as images, text, and audio to extract features and establish search queries, allowing for dynamic visual searches that retrieve results based on physical characteristics without pre-tagged metadata, using pattern recognition and indexing mechanisms to facilitate efficient retrieval of relevant data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional text-centric search engines use pre-indexed metadata and manual tagging, then search results can be retrieved, but the search process becomes time-consuming and frustrating requiring iterative keyword adjustments
Solution Approach 1:
The patent replaces manual text-based search mechanisms with automated image analysis and pattern recognition systems. Instead of requiring users to manually input keywords and iteratively adjust queries, the system automatically analyzes uploaded images to extract visual features, objects, and context, then generates search queries and retrieves relevant results automatically, eliminating the time-consuming manual search process
Solution Approach 2:
The system enables self-service search by automatically analyzing uploaded images and generating appropriate search queries without user intervention. The image analysis component automatically extracts features, identifies objects, and formulates search terms, allowing the system to serve itself rather than requiring users to manually construct and refine text queries
2Adaptability or versatility
If search engines rely on pre-tagged metadata, then indexing is simplified, but the system cannot search for visual attributes that were not manually tagged
Solution Approach 1:
The system performs preliminary action by automatically analyzing images and extracting visual features before the search process begins. The image analysis component pre-processes uploaded images to identify objects, colors, shapes, and context, creating a rich feature representation that can be used for versatile search queries without requiring pre-tagged metadata
Solution Approach 2:
The patent substitutes manual metadata tagging with automated computer vision and pattern recognition systems. Instead of relying on pre-tagged metadata, the system uses image analysis algorithms to automatically extract visual attributes, enabling search for any visual characteristic without manual intervention in the indexing process
3Measurement precision
If users manually input keywords and Boolean operators, then search queries can be precise, but the process becomes complex and time-consuming
Solution Approach 1:
The system performs self-service by automatically analyzing uploaded images and generating precise search queries without requiring user input of keywords or Boolean operators. The image analysis component extracts visual features and automatically formulates search terms that capture the essence of the image, eliminating the complexity of manual query construction while maintaining search precision
Solution Approach 2:
The system introduces an intermediary - the image analysis component - that translates visual information into search queries. This intermediary automatically extracts features from uploaded images and converts them into appropriate search terms, acting as a bridge between the user's visual input and the search system without requiring users to manually construct queries
Data Source
AI summary
A system that can analyze a multi-dimensional input thereafter establishing a search query based upon extracted features from the input. In a particular example, an image can be used as an input to a search mechanism. Pattern recognition and image analysis can be applied to the image thereafter establishing a search query that corresponds to features extracted from the image input. The system can also facilitate indexing multi-dimensional searchable items thereby making them available to be retrieved as results to a search query. More particularly, the system can employ text analysis, pattern and/or speech recognition mechanisms to extract features from searchable items. These extracted features can be employed to index the searchable items.