Name
Title | ||
|---|---|---|
Similarity Measure of the Visual Features Using the Constrained Hierarchical Clustering for Content Based Image Retrieval |
Abstract | ||
|---|---|---|
In this paper, we present a methodology on how to measure the visual similarity between a query image and hierarchically represented image databases for content based image retrieval. The images in database are hierarchically summarized and classified by recovered extrinsic camera parameters as well as constrained agglomerative clustering methods. The constrained agglomerative hierarchical image clustering method whose strategy is to extract a multi-level partitioning and grouping of multiple images is used for balancing the hierarchical trees and summarization. The visual codebooks which are hierarchically quantized in the clusters are used to calculate the similarity measure with a query image's visual features. Our proposed visual similarity measure and summarization of image data provide a very efficient way for searching and retrieving the images that have similar visual contents and geometrical location. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-89646-3_85 | ISVC |
Keywords | Field | DocType |
similarity measure,constrained hierarchical clustering,image data,query image,visual codebooks,multiple image,image databases,image retrieval,visual feature,agglomerative hierarchical image,similar visual content,proposed visual similarity measure,hierarchical clustering | Hierarchical clustering,Data mining,Automatic image annotation,Pattern recognition,Similarity measure,Computer science,Image retrieval,Consensus clustering,Artificial intelligence,Brown clustering,Content-based image retrieval,Visual Word | Conference |
Volume | ISSN | Citations |
5359 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 10 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sang Min Yoon | 1 | 129 | 19.66 |
| Holger Graf | 2 | 56 | 15.10 |