Image Database Update Server Selective Feature Indexing
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Solution Overview
Problem
Conventional image database updating processes are inefficient as they require excessive processing time due to updating both existing and newly added images together, often resulting in prolonged processing times during idle periods.
Innovation Solution
A method and system that selectively update only newly added or modified images in the image database by using an image updating server to extract and store features of updated images, associating them with a search engine, and maintaining an image update table to track modifications, thereby reducing unnecessary processing of unchanged images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing images and newly added images are updated together in the image database, then the database remains up-to-date, but the processing time becomes excessively long
Solution Approach 1:
The patent segments the image update process into two distinct groups: existing images and newly added images. By separating these groups, the system can apply different update strategies to each, processing only the necessary new images rather than reprocessing all images in the database, thus reducing processing time while maintaining database up-to-dateness.
Solution Approach 2:
The patent extracts only the newly added images from the entire image database for processing. By taking out only the relevant new images and excluding existing images from the update process, the system achieves database updates without the excessive processing time associated with processing all images.
2Reliability
If all images in the database are processed during idle periods, then the search results are most up-to-date, but the processing efficiency decreases
Solution Approach 1:
The patent applies partial action by processing only the necessary new images rather than all images in the database. This selective processing maintains search result freshness for new content while significantly improving processing efficiency by avoiding unnecessary operations on existing images.
Solution Approach 2:
The system uses an image update table to track which images are new and need processing. This self-service mechanism allows the database to automatically identify and process only the necessary images, maintaining freshness without requiring full database processing, thus improving efficiency.
3Device complexity
If the image update process includes both existing and new images, then the database structure remains simple, but the processing time becomes excessively long
Solution Approach 1:
The patent introduces an image update table as a preliminary structure to track new images before processing. This preliminary action of recording new image information allows the system to later process only those specific images, maintaining database structure simplicity while dramatically reducing processing time through targeted updates.
Data Source
AI summary
Updating images in an image database includes determining an updated image that is among a plurality of images in the image database, extracting a plurality of image features of the updated image and storing a plurality of image feature values that correspond to the plurality of image features, and associating the plurality of image features of the updated image with a search engine, including adding an array comprising the plurality of image feature values to an index of the search engine.