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salman Ahmadi

salman Ahmadi

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0003-4281-1971
Education: PhD.
ScopusId: 57190510344
Faculty: Faculty of Engineering
Address:
Phone:

Research

Title
AUTOMATIC BUILDING EXTRACTION FROM HIGH RESOLUTION AERIAL IMAGES USING ACTIVE CONTOUR MODEL
Type
Presentation
Keywords
Building Extraction، Active Contours
Year
2008
Researchers salman Ahmadi ، Hamid Ebadi ، mohammad javad Valadan Zoej ، Hamid Abrishami Moghaddam

Abstract

Various governmental organizations need accurate, correct and up to date information for optimization of resource and service management. In this issue, geospatial information is very important. Geospatial information as essential part of Geospatial Information System (GIS) has important role in performance of civil projects, urban service management. Using conventional surveying methods for producing geospatial data require a lot of cost and time. Thus, utilization of modern methods in production and updating of this kind of data is necessary.Photogrammetry and Remote Sensing are methods that produce geospatial data in extensive area with acceptable accuracy. In various countries of the world, many researches have been carried out and many algorithms have been introduced in order to decrease human operation in automatic feature extraction of satellite images. Building is one of the features that take the maximum of time and cost of feature extraction due to its abundance in urban area. As a result, on access to a model or algorithm of automatic or semi-automatic extraction of this feature not only minimizes human role in producing large scale maps but also has a dramatic effect on time and cost of the project. The aim of this paper is automatic extraction of boundary of this feature from high resolution aerial images in a way that its output is a vector map that needs the least editing in GIS the main goal of this research is to introduce a method based on active contour model that the initialization stage of algorithm can be carried out automatically and active contour be ultimately optimized in building extraction. A new model is also suggested for automatic detection and extraction of boundary of buildings. New model of active contour can detect and extract boundary of building very accurately compared to classical model of active contour model and avoid detection of the boundary of features that are in neighbor of buildings such as streets and trees. The result