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Qatris iManager: a general purpose CBIR system

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Qatris iManager: a general purpose CBIR system

Content Provider	Springer Nature Link
Author	Barrena, M. Alonso, T. Caro, A. Rodríguez, P. G. Arias Nicolás, J. P. Durán, M. L.
Copyright Year	2015
Abstract	Content-based image retrieval (CBIR) has drawn much interest from the research community over the past decade, as a good number of CBIR techniques, methods and systems have emerged, contributing new solutions to the issue of storing, managing and retrieving images, as database management systems do with structured data. There is undoubtedly a crucial need to characterize image content as well as subjectivity in the interpretation of this content (for which the community has coined the term “semantic gap”). In this paper the CBIR system developed by our research group, Qatris iManager, is described as a positive proposal to cope with chief issues in the field, especially the semantic gap, from a novel and original perspective. Based on color, texture and shape features, our system provides a broad range of useful operations to facilitate the storage, management, retrieval and browsing of large image collections. Local and remote image loading processes enable the population of image collections. Classification methods allow users to organize the collections according to their own interests. A multidimensional access method contributes to the efficiency in similarity searches. Parameterized similarity functions give flexibility to the search by content processes. Finally, the integrated automatic learning methods for classification and search processes teach the system about the user’s information needs. The proposed system is the result of a joint effort with different research tasks. This paper extensively describes all the system functionalities, techniques, processes and algorithms implemented.
Ending Page	442
Page Count	20
Starting Page	423
File Format	PDF
ISSN	09328092
e-ISSN	14321769
Journal	Machine Vision and Applications
Issue Number	4
Volume Number	26
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-03-26
Publisher Place	Berlin/Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Information storage and retrieval Relevance feedback Automatic learning Pattern Recognition Content-based image retrieval (CBIR) Semantic gap Image Processing and Computer Vision Feature extraction Searching and sorting Communications Engineering, Networks Indexing Image classification
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Computer Science Applications Software Hardware and Architecture

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Semantic content based image retrieval technique using cloud computing

Automatic Feature Weight Determination using Indexing and Pseudo-Relevance Feedback for Multi-feature Content-Based Image Retrieval

Multi-modal CBIR Algorithm Based on Latent Semantic Indexing

Time comparison of various feature extraction of content based image retrieval.

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An image semantic retrieval system design and realization

Fighting the Semantic Gap on CBIR Systems through New Relevance Feedback Techniques

An effective technique for the content based image retrieval to reduce the semantic gap based on an optimal classifier technique

Efficient Semantic Indexing for Image Retrieval

Qatris iManager: a general purpose CBIR system

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Qatris iManager: a general purpose CBIR system