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Subject and Keywords:
Intuicjonistyczne zbiory rozmyte ; Intuitionistic fuzzy sets ; Possibility theory ; Teoria możliwości ; System wyszukiwania obrazów po zawartości cbir ; Obiekt graficzny ; Indeksowanie obrazów ; Klasyfikacja obrazów ; Content-based image retrieval system ; Graphical object ; Image indexing ; Image classification
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 these researches is to provide effective and efficient means for the semantic interpretation of graphical objects. 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.
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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.
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Click the link below to view the content.https://www.ibspan.waw.pl/~alex/OZwRCIN/WA777_114495_RB-2009-40_Some Aspects of Intuitionistic Fuzzy Sets and Possibility Theory as an Approach to Graphical Object Semantics for CBIR._content.pdf