Image Search Feature Vector Clustering
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Solution Overview
Problem
Conventional image searching methods face challenges in accuracy and efficiency due to the difficulty in describing images with keywords, varying user assignments of keywords, and the inefficiency of feature vector-based approaches with large image datasets.
Innovation Solution
A system and method that determine a target feature vector for a target image and feature vectors for multiple images, creating a search region in an N-dimensional feature space based on a preset similarity range to identify similar images by selecting candidate images within this region and ranking them by similarity degree.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If feature vector-based image searching is used, then image searching accuracy is improved, but searching efficiency deteriorates when the number of images is large
Solution Approach 1:
The patent segments the image database into multiple clusters based on feature vectors, creating a hierarchical search structure. Instead of comparing the target image with all images in the database, the system first identifies relevant clusters and then performs detailed comparisons only within those clusters. This segmentation approach maintains high search accuracy while dramatically improving efficiency by reducing the number of comparisons needed in large datasets.
2Productivity
If textual meta-information is used for image searching, then searching speed is improved, but searching accuracy deteriorates
Solution Approach 1:
The patent performs preliminary extraction of feature vectors from images and organizes them into clusters before the actual search operation. This preliminary action creates a structured framework that enables fast retrieval. During the search phase, the system uses this pre-organized structure to quickly identify relevant image groups, achieving both high speed and high accuracy by combining efficient preprocessing with targeted comparison.
Data Source
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AI summary
A system and a method for image searching. The method may include obtaining a target image and a plurality of images, wherein at least one similar image to the target image is to be searched from the plurality of images. The method may include determining a target feature vector of the target image and a feature vector of each of the plurality of images, each of the target feature vector and the feature vectors being an N-dimensional feature vector in an N-dimensional feature space. The method may include determining a search region in the N-dimensional feature space. The method may include determining one or more candidate images, the feature vector of each candidate image being within the search region. The method may further include determining the at least one similar image to the target image among the one or more candidate images.