Image Search Indexing via User Annotation Content

The patent applies preliminary action by pre-processing images to extract visual features and pre-generating visual indexes before actual search queries are submitted. The server performs feature extraction and index building in advance, so that when users submit search images, the system can quickly compare against pre-computed visual features rather than analyzing images in real-time during search operations.

The patent introduces visual features as an intermediary between the image data and the search query mechanism. Instead of directly comparing filenames or performing complex image analysis during search, the system uses extracted visual features (color histograms, texture descriptors, shape features) as intermediate representations that enable efficient similarity comparison and expand search capabilities beyond simple filename matching.

The patent applies universality by designing the visual index structure to serve multiple functions simultaneously. The same visual feature extraction and indexing mechanism supports both image similarity search and annotation-based search. The index can be queried using either visual features from upload images or annotation content, making the system multi-functional without requiring separate processing pipelines for each search type.

The patent segments the image data processing into distinct components: visual feature extraction, annotation content processing, and index generation. Each component handles specific aspects of image information independently, allowing the system to manage complexity by dividing the overall processing task into manageable segments that can be optimized and maintained separately.