Title
New content based image retrieval database structure using query by approximate shapes
Abstract
The image retrieval from multimedia databases is a very challenging problem nowadays. Not only it requires the proper query form, but also efficient methods of data storage. The problem is important, because nowadays there are many different systems which needs image retrieval. As an example web searching engines may be given, which had to store a very huge amount of images and needs fast image retrieval of chosen ones. Also social media portals increasingly face the same requirements. This paper presents a new Content Based Image Retrieval database. It is based on new object representation which is based on approximation of objects by a set of shapes. The structure of the database is designed in order to reduce the number of comparisons using a tree structure. The main advantages of the proposed solution are: easy queries for users, faster image retrieval and ability to parallelize queries.
Year
DOI
Venue
2017
10.15439/2017F457
2017 Federated Conference on Computer Science and Information Systems (FedCSIS)
Keywords
Field
DocType
data storage,approximate shapes,multimedia databases,content based image retrieval database structure,query form,social media portals,object representation
Data mining,Automatic image annotation,Human–computer information retrieval,Information retrieval,Query expansion,Feature detection (computer vision),Computer science,Image retrieval,Tree structure,Content-based image retrieval,Visual Word
Conference
ISSN
ISBN
Citations 
2325-0348
978-1-5090-4414-6
1
PageRank 
References 
Authors
0.36
13
2
Name
Order
Citations
PageRank
Stanislaw Deniziak14513.20
T. Michno272.87