Image Selection System Using Temporal Gap Extraction
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Solution Overview
Problem
Users face difficulties in quickly determining the contents of large image storage devices such as CDs, DVDs, and hard disk drives, as existing methods require manual sorting through numerous images or printing limited thumbnails, making it hard to identify specific images among thousands.
Innovation Solution
A method that groups images based on parameters like time, place, or content, allowing users to select a representative subset of images for display, such as the first and last images of each sequence, and the largest time gaps, enabling efficient identification of stored images without displaying all images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all images are displayed to show complete storage contents, then information completeness is improved, but user time and operational complexity worsen
Solution Approach 1:
The patent extracts and displays only the most representative images (first image, last image, and images at largest time gaps) from the complete storage set, rather than showing all images. This extraction principle allows users to understand the full temporal scope of stored images while minimizing the number of images that need to be viewed, thus resolving the contradiction between information completeness and user time.
2Loss of information
If all images are displayed to show complete storage contents, then information completeness is improved, but device complexity and operational difficulty worsen
Solution Approach 1:
The system automatically extracts key representative images based on time gap analysis, eliminating the need for manual sorting or browsing through all images. This automated extraction reduces operational complexity while maintaining information completeness about the storage contents.
Solution Approach 2:
The system performs self-service by automatically analyzing the image set, identifying time gaps, and selecting representative images without requiring user intervention for sorting or selection. This self-organizing capability reduces the operational burden on users while providing comprehensive storage overview.
3Ease of operation
If manual sorting methods are used to organize images, then image organization is improved, but user time and operational complexity worsen
Solution Approach 1:
The system automatically organizes images by performing self-service sorting based on time gap analysis. It identifies representative images that naturally divide the chronologically sorted image set into meaningful groups, eliminating the need for manual user sorting while achieving effective image organization.
Solution Approach 2:
The system changes the organizational parameter from manual user-defined categories to automated time-gap-based selection. By using time gaps as the organizing parameter, the system automatically groups images into meaningful temporal segments without requiring users to define custom sorting criteria, thus improving ease of operation while reducing time investment.
Data Source
AI summary
A method for efficiently allowing users to select or view images from a large quantity of images that are stored on various medias. The method groups images according to specific parameters and displays a sub set of these parameters allowing users to quickly select or determine if the image that they are seeking is in that particular storage area or media.