Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Automated building detection from satellite images by using shadow information as an object invariant
Download
index.pdf
Date
2012
Author
Yüksel, Barış
Metadata
Show full item record
Item Usage Stats
345
views
128
downloads
Cite This
Apart from classical pattern recognition techniques applied for automated building detection in satellite images, a robust building detection methodology is proposed, where self-supervision data can be automatically extracted from the image by using shadow and its direction as an invariant for building object. In this methodology; first the vegetation, water and shadow regions are detected from a given satellite image and local directional fuzzy landscapes representing the existence of building are generated from the shadow regions using the direction of illumination obtained from image metadata. For each landscape, foreground (building) and background pixels are automatically determined and a bipartitioning is obtained using a graph-based algorithm, Grabcut. Finally, local results are merged to obtain the final building detection result. Considering performance evaluation results, this approach can be seen as a proof of concept that the shadow is an invariant for a building object and promising detection results can be obtained when even a single invariant for an object is used.
Subject Keywords
Image processing
,
Remote-sensing images.
,
Pattern recognition systems.
,
Graph algorithms.
,
Markov random fields.
URI
http://etd.lib.metu.edu.tr/upload/12614909/index.pdf
https://hdl.handle.net/11511/21823
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
A Shadow based trainable method for building detection in satellite images
Dikmen, Mehmet; Halıcı, Uğur; Department of Geodetic and Geographical Information Technologies (2014)
The purpose of this thesis is to develop a supervised building detection and extraction algorithm with a shadow based learning method for high-resolution satellite images. First, shadow segments are identified on an over-segmented image, and then neighboring shadow segments are merged by assuming that they are cast by a single building. Next, these shadow regions are used to detect the candidate regions where buildings most likely occur. Together with this information, distance to shadows towards illuminati...
Automatic building extraction from high resolution satellite images for map updating: A model based approach
San, D. Koc; TÜRKER, MUSTAFA (2007-10-12)
An approach was developed for automatically updating the buildings of an existing vector database from high resolution satellite images using spectral image classification, Digital Elevation Models (DEM) and the model-based extraction techniques. First, the areas that contain buildings are detected using spectral image classification and the normalized Digital Surface Model (nDSM). The classified output provides the shapes and the approximate locations of the buildings. However, those buildings that have si...
Alignment of uncalibrated images for multi-view classification
Arık, Sercan Ömer; Vural, Elif; Frossard, Pascal (2011-12-29)
Efficient solutions for the classification of multi-view images can be built on graph-based algorithms when little information is known about the scene or cameras. Such methods typically require a pairwise similarity measure between images, where a common choice is the Euclidean distance. However, the accuracy of the Euclidean distance as a similarity measure is restricted to cases where images are captured from nearby viewpoints. In settings with large transformations and viewpoint changes, alignment of im...
Image fusion for improving spatial resolution of multispectral satellite images
Ünlüsoy, Deniz; Süzen, Mehmet Lütfi; Department of Geological Engineering (2013)
In this study, four different image fusion techniques have been applied to high spectral and low spatial resolution satellite images with high spatial and low spectral resolution images to obtain fused images with increased spatial resolution, while preserving spectral information as much as possible. These techniques are intensity-hue-saturation (IHS) transform, principle component analysis (PCA), Brovey transform (BT), and Wavelet transform (WT) image fusion. Images used in the study belong to Çankırı reg...
Analysis of near-field ultra-wideband radar imaging algorithms
Arabacı, Ahmet; Koç, Seyit Sencer; Department of Electrical and Electronics Engineering (2017)
Recently, near-field ultra-wideband radar imaging algorithms have an important place in short range imaging applications by providing high resolution in both range and cross-range. In this study, the near-field ultra-wideband radar imaging algorithms in the literature such as Holographic Image Reconstruction Algorithm, Range Migration Algorithm, MIMO Based Range Migration Algorithm and MIMO Based Kirchhoff Migration Algorithm have been implemented using MATLAB. The algorithms are applied to modeled transmit...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. Yüksel, “Automated building detection from satellite images by using shadow information as an object invariant,” M.S. - Master of Science, Middle East Technical University, 2012.