A region-based level set segmentation for automatic detection of Man-made objects from aerial and satellite images

Karantzalos, K; Argialas, D

dc.contributor.author	Karantzalos, K	en
dc.contributor.author	Argialas, D	en
dc.date.accessioned	2014-03-01T01:29:37Z
dc.date.available	2014-03-01T01:29:37Z
dc.date.issued	2009	en
dc.identifier.issn	0099-1112	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19329
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-67650869552&partnerID=40&md5=feffb5c8eada755ca261466836b7e6c6	en
dc.subject.classification	Geography, Physical	en
dc.subject.classification	Geosciences, Multidisciplinary	en
dc.subject.classification	Remote Sensing	en
dc.subject.classification	Imaging Science & Photographic Technology	en
dc.subject.other	Automatic Detection	en
dc.subject.other	Geometric form	en
dc.subject.other	Image partition	en
dc.subject.other	Initial contour	en
dc.subject.other	Level set segmentation	en
dc.subject.other	Man made objects	en
dc.subject.other	Number of iterations	en
dc.subject.other	Quantitative evaluation	en
dc.subject.other	Real-time application	en
dc.subject.other	Region-based	en
dc.subject.other	Satellite images	en
dc.subject.other	Statistical descriptions	en
dc.subject.other	Variational models	en
dc.subject.other	Curve fitting	en
dc.subject.other	Level measurement	en
dc.subject.other	Satellites	en
dc.subject.other	Object recognition	en
dc.subject.other	aerial survey	en
dc.subject.other	algorithm	en
dc.subject.other	automation	en
dc.subject.other	detection method	en
dc.subject.other	experimental study	en
dc.subject.other	manmade structure	en
dc.subject.other	modeling	en
dc.subject.other	photogrammetry	en
dc.subject.other	qualitative analysis	en
dc.subject.other	quantitative analysis	en
dc.subject.other	remote sensing	en
dc.subject.other	satellite imagery	en
dc.subject.other	segmentation	en
dc.title	A region-based level set segmentation for automatic detection of Man-made objects from aerial and satellite images	en
heal.type	journalArticle	en
heal.language	English	en
heal.publicationDate	2009	en
heal.abstract	A region-based level set segmentation was developed for the automatic detection of man-made objects from aerial and satellite images. The essence of the approach is to optimize the position and the geometric form of an evolving curve, by measuring information within the regions that compose a particular image partition based on their statistical description. The present region-based variational model is fully automated without the need to manually specify the position of the initial contour. Furthermore, it converges after a small number of iterations, allowing real-time applications. The developed algorithm was tested for the detection of roads, buildings and other man-made objects in a number of aerial and satellite images. The effectiveness of the algorithm is demonstrated by the experimental results and the performed qualitative and quantitative evaluation. © 2009 American Society for Photogrammetry and Remote Sensing.	en
heal.publisher	AMER SOC PHOTOGRAMMETRY	en
heal.journalName	Photogrammetric Engineering and Remote Sensing	en
dc.identifier.isi	ISI:000266707600006	en
dc.identifier.volume	75	en
dc.identifier.issue	6	en
dc.identifier.spage	667	en
dc.identifier.epage	677	en