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Pregled bibliografske jedinice broj: 781697

Časopis

Autori: Ivašić-Kos, Marina; Ipšić, Ivo; Ribarić, Slobodan
Naslov: A knowledge-based multi-layered image annotation system
( A knowledge-based multi-layered image annotation system )
Izvornik: Expert systems with applications (0957-4174) 42 (2015), 2015; 9539-9553
Vrsta rada: članak
Ključne riječi: Image annotation; Multi-layered image annotation; Knowledge representation; Fuzzy Petri Net; Fuzzy inference engine
( Image annotation; Multi-layered image annotation; Knowledge representation; Fuzzy Petri Net; Fuzzy inference engine )
Sažetak:
Major challenge in automatic image annotation is bridging the semantic gap between the computable low-level image features and the human-like interpretation of images. The interpretation includes concepts on different levels of abstraction that cannot be simply mapped to features but require additional reasoning with general and domain-specific knowledge. The problem is even more complex since knowledge in context of image interpretation is often incomplete, imprecise, uncertain and ambiguous in nature. Thus, in this paper we propose a fuzzy-knowledge based intelligent system for image annotation, which is able to deal with uncertain and ambiguous knowledge and can annotate images with concepts on different levels of abstraction that is more human-like. The main contributions are associated with an original approach of using a fuzzy knowledge-representation scheme based on the Fuzzy Petri Net (KRFPN) formalism. The acquisition of knowledge is facilitated in a way that besides the general knowledge provided by the expert, the computable facts and rules about the concepts, as well as their reliability, are produced automatically from data. The reasoning capability of the fuzzy inference engine of the KRFPN is used in a novel way for inconsistency checking of the classified image segments, automatic scene recognition, and the inference of generalized and derived classes. The results of image interpretation of Corel images belonging to the domain of outdoor scenes achieved by the proposed system outperform the published results obtained on the same image base in terms of average precision and recall. Owing to the fuzzy- knowledge representation scheme, the obtained image interpretation is enriched with new, more general and abstract concepts that are close to concepts people use to interpret these images. Highlights: • A fuzzy-knowledge based intelligent system for multilayered image annotation. • Novel merged statistical and knowledge-based approach for image interpretation. • Automatic acquisition of facts and rules about the concepts, and their reliability. • Inconsistency checking of image segments classification. • Automatic knowledge- based scene recognition and inference of more abstract classes.
Projekt / tema: HRZZ-IP-2013-11-6733
Izvorni jezik: eng
Rad je indeksiran u
bazama podataka:
Current Contents Connect (CCC)
Scopus
SCI-EXP, SSCI i/ili A&HCI
Science Citation Index Expanded (SCI-EXP) (sastavni dio Web of Science Core Collectiona)
Kategorija: Znanstveni
Znanstvena područja:
Računarstvo,Informacijske i komunikacijske znanosti
Puni text rada: 781697.ESWA-1-s2.0-S095741741500528X-main.pdf (tekst priložen 31. Ožu. 2016. u 11:18 sati)
URL Internet adrese: http://www.sciencedirect.com/science/article/pii/S095741741500528X
Broj citata:
Altmetric:
DOI: 10.1016/j.eswa.2015.07.068
URL cjelovitog teksta:
Google Scholar: A knowledge-based multi-layered image annotation system
Upisao u CROSBI: Marina Ivašić (Marina.Ivasic@inf.uniri.hr), 15. Lis. 2015. u 16:00 sati



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