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 Computationally Efficient Appearance-Based Algorithm for Geospatial Object Detection
Date
2012-04-27
Author
Arslan, Duygu
Alatan, Abdullah Aydın
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
272
views
0
downloads
Cite This
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 utilized for detecting aircrafts in various orientations. Experiments are conducted on satellite images taken from various airport regions and promising results are obtained. Among tested various satellite images of 0.5 m resolution including 300 target aircrafts of various sizes, the proposed algorithm has resulted with typical values of 77% and 85% for precision and recall, respectively.
Subject Keywords
Geospatial object detection
,
Integral image
,
Aircraft operator
URI
https://hdl.handle.net/11511/40182
DOI
https://doi.org/10.1117/12.920272
Conference Name
Conference on Optical Pattern Recognition XXIII
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
An automatic geo-spatial object recognition algorithm for high resolution satellite images
Ergul, Mustafa; Alatan, Abdullah Aydın (2013-09-26)
This paper proposes a novel automatic geo-spatial object recognition algorithm for high resolution satellite imaging. The proposed algorithm consists of two main steps; a hypothesis generation step with a local feature-based algorithm and a verification step with a shape-based approach. In the hypothesis generation step, a set of hypothesis for possible object locations is generated, aiming lower missed detections and higher false-positives by using a Bag of Visual Words type approach. In the verification s...
A Fully automatic shape based geo-spatial object recognition
Ergül, Mustafa; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2012)
A great number of methods based on local features or global appearances have been proposed in the literature for geospatial object detection and recognition from satellite images. However, since these approaches do not have enough discriminative capabilities between object and non-object classes, they produce results with innumerable false positives during their detection process. Moreover, due to the sliding window mechanisms, these algorithms cannot yield exact location information for the detected object...
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...
A Novel Neural Network Method for Direction of Arrival Estimation with Uniform Cylindrical 12-Element Microstrip Patch Array
Caylar, Selcuk; Dural, Guelbin; Leblebicioğlu, Mehmet Kemal (2008-01-01)
In this study a new neural network algorithm is proposed for real time multiple source tracking problem with cylindrical patch antenna array based on a previous v reported Modified Neural Multiple Source Tracking Algorithm(MN-MUST). The proposed algorithm, namely Cylindrical Microstrip Patch Array Modified Neural Multiple Source Tracking Algorithm (CMN-MUST) implements W-MUST algorithm on a cylindrical microsttip patch array structure. CMN-MUST algorithm uses the advantage of directive pattern of microstrip...
A multimodal approach for individual tracking of people and their belongings
Beyan, Çiğdem; Temizel, Alptekin (2015-04-01)
In this study, a fully automatic surveillance system for indoor environments which is capable of tracking multiple objects using both visible and thermal band images is proposed. These two modalities are fused to track people and the objects they carry separately using their heat signatures and the owners of the belongings are determined. Fusion of complementary information from different modalities (for example, thermal images are not affected by shadows and there is no thermal reflection or halo effect in...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
D. Arslan and A. A. Alatan, “A Computationally Efficient Appearance-Based Algorithm for Geospatial Object Detection,” Baltimore, MD, 2012, vol. 8398, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40182.