An edge-region cooperative multi-agent approach for buildings extraction

This paper presents a new approach for automatic building detection in very high resolution satellite images. The proposed method is a cooperative multi-agent approach between both an edge and region approach. In the pretreatment step, a supervisor agent finds a building's corner using Harris detector. Starting from these points, a cooperation process is used to extract buildings. Experiments are done on images of Strasbourg city taken by Quickbird.

[1]  Salman Ahmadi,et al.  An improved snake model for automatic extraction of buildings from urban aerial images and LiDAR data , 2010, Comput. Environ. Urban Syst..

[2]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[3]  Raymond Chiong,et al.  An improved snake for automatic building extraction , 2007 .

[4]  Jing Peng,et al.  An improved snake model for building detection from urban aerial images , 2005, Pattern Recognit. Lett..

[5]  Hmida Rojbani,et al.  Rθ-signature: A new signature based on Radon Transform and its application in buildings extraction , 2011, 2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).

[6]  M. Turker,et al.  Automatic building detection from high resolution satellite images , 2005, Proceedings of 2nd International Conference on Recent Advances in Space Technologies, 2005. RAST 2005..

[7]  J. Weber,et al.  Automatic Building Extraction in VHR Images Using Advanced Morphological Operators , 2007, 2007 Urban Remote Sensing Joint Event.

[8]  Dong-Chen He,et al.  A new approach to building identification from very‐high‐spatial‐resolution images , 2009 .

[9]  Heinz Rüther,et al.  Application of snakes and dynamic programming optimisation technique in modeling of buildings in informal settlement areas , 2002 .

[10]  D. Boulmier,et al.  Segmentation 3D multi-objets d'images scanner cardiaques : une approche multi-agents 3D Multi-Object Segmentation of Cardiac MSCT Imaging by using a Multi- Agent Approach , 2009 .

[11]  Dong-Chen He,et al.  Automatic change detection of buildings in urban environment from very high spatial resolution images using existing geodatabase and prior knowledge , 2010 .

[12]  F. D. Garber,et al.  The Quality of Training Sample Estimates of the Bhattacharyya Coefficient , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Hadjer Laguel Déploiement sur une plate-forme de visualisation d'un algorithme coopératif pour la segmentation d'images IRM autour d'un système multi-agents. (Deployment on a visualization platform of a cooperative algorithm for MRI images segmentation over a multi-agent system) , 2010 .

[14]  Hamid Ebadi,et al.  Automated Building Extraction from High-Resolution Satellite Imagery Using Spectral and Structural Information Based on Artificial Neural Networks , 2007 .

[15]  Curt H. Davis,et al.  Automated Building Extraction from High-Resolution Satellite Imagery in Urban Areas Using Structural, Contextual, and Spectral Information , 2005, EURASIP J. Adv. Signal Process..

[16]  R. Crippen Calculating the vegetation index faster , 1990 .