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Titolo:
Differential snakes for change detection in road segments
Autore:
Agouris, P; Stefanidis, A; Gyftakis, S;
Indirizzi:
Univ Maine, Dept Spatial Informat Engn, Orono, ME 04469 USA Univ Maine Orono ME USA 04469 Spatial Informat Engn, Orono, ME 04469 USA Univ Maine, Natl Ctr Geog Informat & Anal, Orono, ME 04469 USA Univ MaineOrono ME USA 04469 r Geog Informat & Anal, Orono, ME 04469 USA
Titolo Testata:
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
fascicolo: 12, volume: 67, anno: 2001,
pagine: 1391 - 1399
Fonte:
ISI
Lingua:
ENG
Soggetto:
LINEAR FEATURE-EXTRACTION;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
22
Recensione:
Indirizzi per estratti:
Indirizzo: Agouris, P Univ Maine, Dept Spatial Informat Engn, 348 Boardman Hall, Orono, ME 04469USA Univ Maine 348 Boardman Hall Orono ME USA 04469 no, ME 04469USA
Citazione:
P. Agouris et al., "Differential snakes for change detection in road segments", PHOTOGR E R, 67(12), 2001, pp. 1391-1399

Abstract

The automation of object extraction from digital imagery has been a key research issue in digital photogrammetry and computer vision. In the spatiotemporal context of modern GIS, with constantly changing environments and periodic database revisions, change detection is becoming increasingly important. In this paper, we present a novel approach for the integration of object extraction and image-based geospatial change detection. We extend the model of deformable contour models (snakes) to function in a differential mode, and introduce a new framework to differentiate change detection from the recording of numerous slightly different versions of objects that may remain unchanged. We assume the existence of prior information for an object (anolder record of its shape available in a GIS) with accompanying accuracy estimates. This information becomes input for our "differential snakes" approach. In a departure from standard techniques, the objective of our object extraction is not to extract yet another version of an object from the new image, but instead to update the preexisting GIS information (shape and corresponding accuracy). By incorporating accuracy information in our technique, we identify local or global changes to this prior information, and update the GIS database accordingly. This process is complemented by versioning,where, in the absence of change, the pre-existing information may be improved in terms of accuracy if the new image so permits. Experimental results (using synthetic and real images) are presented to demonstrate the performance of our approach.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 02/04/20 alle ore 05:23:33