Content-based retrieval using invariant features, self-organizing maps, concepts and fuzzy interval numbers

dc.contributor.author	Βασιλάς, Νικόλαος	el
dc.contributor.author	Σκουρλάς, Χρήστος Π.	el
dc.date.accessioned	2015-05-15T14:02:38Z
dc.date.available	2015-05-15T14:02:38Z
dc.date.issued	2015-05-15
dc.identifier.uri	http://hdl.handle.net/11400/10446
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	Ανάκτηση βάση περιεχομένου
dc.subject	αυτο-οργανούμενοι χάρτες
dc.subject	ανάκτηση εικόνων
dc.subject	Content-based image retrieval
dc.subject	Self-organizing maps
dc.subject	images retrieval
dc.title	Content-based retrieval using invariant features, self-organizing maps, concepts and fuzzy interval numbers	en
heal.type	conferenceItem
heal.classification	Τεχνολογία
heal.classification	Πληροφορική
heal.classification	Technology
heal.classification	Computer science
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Πληροφορική
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85133147
heal.classificationURI	http://skos.um.es/unescothes/C00750
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh2008009943
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh99004370
heal.language	en
heal.access	campus
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Πληροφορικής Τ.Ε.	el
heal.publicationDate	2007-09
heal.bibliographicCitation	Skourlas, C. and Vassilas, N. (2007) Content-Based Retrieval Using Invariant Features, Self-Organizing Maps, Concepts and Fuzzy Interval Numbers. The Contribution of Information Technology to Scinece, Economy, Society and Education (eRA-2). Athens, Greece.	en
heal.tableOfContents	In the complex Cross Language Document Retrieval applications dealt in this paper, the goal is to assist the document matching stage when the documents contain images. Hence, we calculate the similarity between a submitted bilingual query and each document in the collection or retrieve images that are similar to a query image, based on features extracted from images. Fuzzy Interval Numbers (FINs) have been employed in various real-world applications including numeric and non-numeric data. In this paper, the use of a FIN classifier is proposed to handle problems of Cross Language Information Retrieval and documents’ classification. The FIN representation of documents is based on the use of the collection term frequency as the term identifier. Such a representation of documents seems to be suitable for Cross Language Information Retrieval without dictionary. In the recent years, Content-Based Image Retrieval (CBIR) evolved to an important research domain within the context of multimodal information retrieval. To assure improved image retrieval performance, even when the images are at different scales and orientations or corrupted by noise, we propose a set of global and local invariant features. Color quantization of the images using self-organizing maps are also used to lead to memory savings and improve, in some cases, image retrieval accuracy.	en
heal.fullTextAvailability	true
heal.conferenceName	The Contribution of Information Technology to Scinece, Economy, Society and Education (eRA-2)	en
heal.conferenceItemType	full paper