Please use this identifier to cite or link to this item: http://hdl.handle.net/11400/3921
Full metadata record
DC FieldValueLanguage
dc.contributor.authorΑσβεστάς, Παντελής Α.ell
dc.contributor.authorΜατσόπουλος, Γεώργιος Κ.ell
dc.contributor.authorΝικήτα, Κωνσταντίνα Σ.ell
dc.date.accessioned2015-01-13T11:40:37Z-
dc.date.available2015-01-13T11:40:37Z-
dc.date.issued2015-01-13-
dc.date.issued1998-
dc.identifier.citationAsvestas, P., Matsopoulos, G. and Nikita, K. (December 1998). A power differentiation method of fractal dimension estimation for 2-D signals. Journal of visual communication and image representation. 9(4). pp. 392–400. Available from: http://www.sciencedirect.com [Accessed 16/04/2002]eng
dc.identifier.urihttp://hdl.handle.net/11400/3921-
dc.description.abstractFractal dimension has been used for texture analysis as it is highly correlated with the human perception of surface roughness. Several methods have been proposed for the estimation of the fractal dimension of an image. One of the most popular is via its power spectrum density, provided that it is modeled as a fractional Brownian function. In this paper, a new method, called the power differentiation method (PDM), for estimating the fractal dimension of a two-variable signal from its power spectrum density is presented. The method is first applied to noise-free data of known fractal dimension. It is also tested with noise-corrupted and quantized data. Particularly, in the case of noise-corrupted data, the modified power differentiation method (MPDM) is developed, resulting in more accurate estimation of the fractal dimension. The results obtained by the PDM and the MPDM are compared directly to those obtained using four other well-known methods of fractal dimension. Finally, preliminary results for the classification of ultrasonic liver images, obtained by applying the new method, are presented.eng
dc.language.isoeng-
dc.publisherAcademic Presseng
dc.rightsΑναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.sourcehttp://store.elsevier.com/en
dc.subjectUltrasonic liver images-
dc.subjectPower differentiation method-
dc.subjectΥπέρηχες εικόνες ήπατος-
dc.subjectΜέθοδος διαφοροποίησης ενέργειας-
dc.titleA power differentiation method of fractal dimension estimation for 2-D signalseng
dc.typeΔημοσίευση σε περιοδικό-
heal.classificationMedicine-
heal.classificationComputer engineering-
heal.classificationΙατρική-
heal.classificationΜηχανική υπολογιστών-
heal.classificationURIhttp://id.loc.gov/authorities/subjects/sh00006614-
heal.classificationURIhttp://id.loc.gov/authorities/subjects/sh85029495-
heal.classificationURI**N/A**-Ιατρική-
heal.classificationURI**N/A**-Μηχανική υπολογιστών-
heal.identifier.secondarydoi:10.1006/jvci.1998.0394-
heal.accessfree-
heal.recordProviderΤ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.ell
heal.journalNameJournal of visual communication and image representationeng
heal.journalTypepeer-reviewed-
heal.fullTextAvailabilitytrue-
Appears in Collections:Δημοσιεύσεις

Files in This Item:
File Description SizeFormat 
A power differentiation method of fractal dimension estimation for 2-D signals.pdf346.74 kBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons