Title:

Developments in fuzzy sets, intuitionistic fuzzy sets, generalized nets and related topics. Volume II: Applications * Aspects of intuitionistic fuzzy sets and possibility theory in graphical object classification for CBIR

Subtitle:

Książka = Book ; KS/6/2010/T2P13

Creator:

Jaworska, Tatiana (1966– )

Publisher:

Instytut Badań Systemowych. Polska Akademia Nauk ; Systems Research Institute. Polish Academy of Sciences

Place of publishing:

Warszawa

Date issued/created:

2010

Description:

[5], 133-148 pages ; 21 cm ; Bibliography p. 146-148

Type of object:

Book/Chapter

Abstract:

This article introduces the imprecision approach to high–level graphical object interpretation. It presents a step towards soft computing which supports the implementation of a content-based image retrieval (CBIR) system dealing with graphical object classification. Some crucial aspects of CBIR are presented here to illustrate the problems that we are now struggling with. The main motivation of our researches is to provide effective and efficient means for the interpretation of graphical object classification. The paper shows how the traditional feature vector method extends to match graphical objects, difficult to classify, by applying intuitionistic fuzzy sets and possibility theory. We consider the cases where both classification of objects and their retrieval are modelled with the aid of fuzzy set extensions.

Relation:

Książka = Book

Resource type:

Text

Detailed Resource Type:

Book

Source:

KS-2010-06-T2P13

Language:

eng

Language of abstract:

eng

Rights:

Creative Commons Attribution BY 4.0 license

Terms of use:

Copyright-protected material. [CC BY 4.0] May be used within the scope specified in Creative Commons Attribution BY 4.0 license, full text available at: ; -

Digitizing institution:

Systems Research Institute of the Polish Academy of Sciences

Original in:

Library of Systems Research Institute PAS

Projects co-financed by:

Operational Program Digital Poland, 2014-2020, Measure 2.3: Digital accessibility and usefulness of public sector information; funds from the European Regional Development Fund and national co-financing from the state budget.

Access:

Open