Generalized multiscale connected operators with applications to granulometric image analysis

Doulamis, A; Doulamis, N; Maragos, P

dc.contributor.author	Doulamis, A	en
dc.contributor.author	Doulamis, N	en
dc.contributor.author	Maragos, P	en
dc.date.accessioned	2014-03-01T02:41:53Z
dc.date.available	2014-03-01T02:41:53Z
dc.date.issued	2001	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30652
dc.subject	Connected Operator	en
dc.subject	Image Analysis	en
dc.subject	Morphological Operation	en
dc.subject	Scale Dependence	en
dc.subject	Size Distribution	en
dc.subject.other	Image reconstruction	en
dc.subject.other	Mathematical models	en
dc.subject.other	Mathematical morphology	en
dc.subject.other	Mathematical operators	en
dc.subject.other	Granulometric image analysis	en
dc.subject.other	Multiscale connected operators	en
dc.subject.other	Multiscale reconstruction	en
dc.subject.other	Image analysis	en
dc.title	Generalized multiscale connected operators with applications to granulometric image analysis	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICIP.2001.958211	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICIP.2001.958211	en
heal.publicationDate	2001	en
heal.abstract	In this paper, generalized granulometric size distributions and size histograms (a.k.a 'pattern spectra') are developed using generalized multiscale lattice operators of the opening and closing type. The generalized size histograms are applied to granulometric analysis of soilsection images. An interesting structure is obtained when the histogram is based on area openings. Furthermore, a fast implementation of the generalized size histograms is presented using threshold analysis-synthesis. Comparisons with size distributions based on conventional morphological operators indicate that the generalized histograms provide a more direct and informative description of the image content in objects with scale-dependent geometric attributes. Applications are also developed for studying the structure of soilsection images.	en
heal.journalName	IEEE International Conference on Image Processing	en
dc.identifier.doi	10.1109/ICIP.2001.958211	en
dc.identifier.volume	3	en
dc.identifier.spage	684	en
dc.identifier.epage	687	en