Coupled geometric and texture PDE-based segmentation

Sofou, A; Evangelopoulos, G; Maragos, P

dc.contributor.author	Sofou, A	en
dc.contributor.author	Evangelopoulos, G	en
dc.contributor.author	Maragos, P	en
dc.date.accessioned	2014-03-01T02:43:11Z
dc.date.available	2014-03-01T02:43:11Z
dc.date.issued	2005	en
dc.identifier.issn	15224880	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31286
dc.subject	Curve Evolution	en
dc.subject	Image Decomposition	en
dc.subject	Natural Scenes	en
dc.subject	Surface Texture	en
dc.subject	Seeded Region Growing	en
dc.subject.other	Energy tracking operators	en
dc.subject.other	Image decomposition	en
dc.subject.other	Modulation components	en
dc.subject.other	Multi frequency filtering	en
dc.subject.other	Texture information	en
dc.subject.other	Feature extraction	en
dc.subject.other	Image quality	en
dc.subject.other	Mathematical models	en
dc.subject.other	Partial differential equations	en
dc.subject.other	Textures	en
dc.subject.other	Image segmentation	en
dc.title	Coupled geometric and texture PDE-based segmentation	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICIP.2005.1530139	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICIP.2005.1530139	en
heal.identifier.secondary	1530139	en
heal.publicationDate	2005	en
heal.abstract	In this paper, along with recent trends in segmentation using multiple image cues, we examine the integration of modulation texture features, image contrast and region size for decomposition of an image in homogenous regions. First, we propose the use of a morphological PDE-based segmentation scheme of the watershed type, based on seeded region-growing and level curve evolution with speed depending on contrast and size. Second, we analyze object surface texture by modelling image variations as local spatial modulation components estimated via multi-frequency filtering and instantaneous energy-tracking operators. By separately exploiting contrast and texture information, through multiscale image decomposition, we propose a PDE-based coupled segmentation method. Experimental results on various classes of images such as soilsections, aerial and natural scenes indicate that the combined effect of image decomposition and multi-cue segmentation improves the overall segmentation process. © 2005 IEEE.	en
heal.journalName	Proceedings - International Conference on Image Processing, ICIP	en
dc.identifier.doi	10.1109/ICIP.2005.1530139	en
dc.identifier.volume	2	en
dc.identifier.spage	650	en
dc.identifier.epage	653	en