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
A Fast shape detection approach by directional integrations
Download
index.pdf
Date
2013
Author
Okman, Osman Erman
Metadata
Show full item record
Item Usage Stats
186
views
121
downloads
Cite This
Detection and identification of objects from aerial images are important problems for various types of application areas. For many of the man-made structures shape is a fundamental feature by which these objects are separated from the background and other structures. In this thesis, a novel geometric shape detection algorithm based on the spatial properties of structures is proposed. Since the objects are transformed into 1-D vectors by evaluating directional integrals and detections occur by the analysis of the features obtained in those 1-D spaces, the proposed approach requires less memory and computation than most of the approaches reported in the literature. Detailed derivation of the method is given and the experimental results are presented in order to show the detection performance of the method under different amount of noise and geometric deformations. Experimental results on real images also show that the proposed approach can significantly speed up the computation without degrading the performance. Moreover, a Petroleum Oil Lubricants (POL) depots identification procedure in high-resolution satellite images is developed where detection of the circular structures is one of the crucial steps, which is achieved by the proposed shape detection approach. Performed experiments over a large data set imply promising identification performance and the usability of the shape detection approach in real world applications.
Subject Keywords
Remote-sensing images.
,
Image processing.
,
Image processing
,
Imaging systems.
,
Image analysis.
URI
http://etd.lib.metu.edu.tr/upload/12616464/index.pdf
https://hdl.handle.net/11511/22884
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...
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...
A Computationally Efficient Appearance-Based Algorithm for Geospatial Object Detection
Arslan, Duygu; Alatan, Abdullah Aydın (2012-04-27)
A computationally efficient appearance-based algorithm for geospatial object detection is presented and evaluated specifically for aircraft detection from satellite imagery. An aircraft operator exploiting the edge information via gray level differences between the aircraft and its background is constructed with Haar-like polygon regions by using the shape information of the aircraft as an invariant. Fast evaluation of the aircraft operator is achieved by means of integral image. Rotated integral images are...
Fast 3D reconstruction from medical image series based on thresholding method Eşikleme metodunu kullanarak medikal görüntü serisinden hizli 3 boyutlu model oluşturma
Öz, Sinan; Serinağaoğlu Doğrusöz, Yeşim (2010-07-15)
Many practical applications in the field of medical image processing need valid, reliable and fast image segmentation. In this study, we propose a semi-automatic segmentation approach. In this approach, an extended version of the Otsu's method for three level thresholding and a recursive connected component algorithm are combined. The segmentation process is accomplished using Extended Otsu's method and labeling in each consecutive slice. Extended Otsu's method is a thresholding method selecting two thresho...
A Gamut-Mapping Framework for Color-Accurate Reproduction of HDR Images
SİKUDOVA, Elena; POULİ, Tania; ARTUSİ, Alessandro; Akyüz, Ahmet Oğuz; BANTERLE, Francesco; Mazlumoglu, Zeynep Miray; REİNHARD, Erik (2016-07-01)
An integrated gamut- and tone-management framework for color-accurate reproduction of high dynamic range images can prevent hue and luminance shifts while taking gamut boundaries into consideration. The proposed approach is conceptually and computationally simple, parameter-free, and compatible with existing tone-mapping operators.
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
O. E. Okman, “A Fast shape detection approach by directional integrations,” Ph.D. - Doctoral Program, Middle East Technical University, 2013.