Image Search via Point-Based Tagging and Relevance Ranking
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Solution Overview
Problem
Current image searching and sorting technologies face challenges with inaccurate content-based searches, high computational costs, and the need for extensive user tagging in tag-based methods, while also failing to efficiently locate specific objects within images.
Innovation Solution
A point-based tagging system that links objects across images using location-specific tags, employing interpolation techniques for object localization and ranking, and a graphical representation to determine image relevance and location, allowing for efficient image registration and display optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If content-based image searching is used, then automatic search capability is improved, but computational cost and processing time increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing image features, color histograms, and spatial relationships in a database before actual search queries. This allows the system to perform rapid searches without performing intensive computations in real-time, thus reducing processing time while maintaining automatic search capability.
Solution Approach 2:
The patent segments the image database into multiple feature categories (color, texture, shape, spatial relationships) and processes search queries by evaluating relevant segments rather than performing complete content analysis on all images. This segmentation reduces computational overhead while preserving automatic search functionality.
2Extent of automation
If content-based image searching is used, then automatic search capability is improved, but computational resources and costs increase
Solution Approach 1:
The system performs computationally intensive feature extraction and image analysis in advance, storing results in optimized data structures. When search queries are received, the system retrieves and compares pre-computed features rather than performing full content analysis, significantly reducing real-time computational resource consumption.
Solution Approach 2:
The patent employs lightweight feature representations and approximate matching techniques that consume minimal computational resources for search operations. Instead of performing expensive pixel-level comparisons, the system uses compact feature vectors and heuristic algorithms that provide satisfactory results with much lower computational cost.
3Reliability
If tag-based image searching is used, then search reliability is improved, but user time and effort increase significantly
Solution Approach 1:
The patent implements self-service by enabling images to automatically generate their own tags and metadata through content analysis algorithms. The system extracts features such as dominant colors, detected objects, and spatial relationships, and uses these to create searchable tags without requiring manual user input, thus maintaining search reliability while eliminating user tagging effort.
Solution Approach 2:
The system uses feedback from user search interactions to automatically refine and improve tagging accuracy over time. By analyzing search patterns and user preferences, the system learns to generate more accurate and relevant tags automatically, further reducing the need for manual tagging while maintaining or improving search reliability.
4Device complexity
If traditional image display organization is used, then simplicity is maintained, but clarity of image relevance and ordering is reduced
Solution Approach 1:
The patent applies local quality by displaying different types of information in different regions of the interface. The display organization presents thumbnail images in one area while simultaneously showing relevance scores, matching tags, and confidence indicators in adjacent areas. This allows the system to maintain visual simplicity while providing comprehensive relevance information without overwhelming the user.
Data Source
AI summary
A web-based application provides more accurate and clearer methods of searching, sorting, and displaying a set of images stored in a database. A first aspect of the present invention is the method by which image data is stored. Typical content-based systems use color information, whereas the present invention uses an image-location tagging method. A second aspect of the present invention is the method by which the set of images are sorted in relevancy. Tag data of the images allows for a new and last method of searching through an entire set. A third aspect of the present invention is the method by which the sorted images are displayed to the user. Instead of the common method of just displaying the images in a rectangular array, where each image is the same size, the web-based application positions and sizes each image based on how relevant it is.