Optimal edge detection using multiple operators for image understanding

<p>Abstract</p> <p>Extraction of features, such as edges for the understanding of aerial images, has been an important objective since the early days of remote sensing. This work aims at describing a new framework which allows for the quantitative combination of a preselected set o...

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Main Authors: Stathaki Tania, Giannarou Stamatia
Format: Article
Language:English
Published: SpringerOpen 2011-01-01
Series:EURASIP Journal on Advances in Signal Processing
Online Access:http://asp.eurasipjournals.com/content/2011/1/28
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spelling doaj-a9f07163228246b4ae71580903b254aa2020-11-24T21:53:58ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802011-01-012011128Optimal edge detection using multiple operators for image understandingStathaki TaniaGiannarou Stamatia<p>Abstract</p> <p>Extraction of features, such as edges for the understanding of aerial images, has been an important objective since the early days of remote sensing. This work aims at describing a new framework which allows for the quantitative combination of a preselected set of edge detectors based on the correspondence between their outcomes. This is inspired from the problem that despite the enormous amount of literature on edge detection techniques, there is no single technique that performs well in every possible image context. Two approaches are proposed for this purpose. The first approach is the well-known receiver operating characteristics analysis which is introduced for a sound quality evaluation of the edge maps estimated by combining different edge detectors. In the second approach, the so-called kappa statistics are employed in a novel fashion to amalgamate the above-mentioned selected edge maps to form an improved final edge image. This method is unique in the sense that the balance between the false detections (false positives and false negatives) is explicitly determined in advance and incorporated in the proposed method in a mathematical fashion. For the performance evaluation of the proposed techniques, a sample set of the RADIUS/DARPA-IU Fort Hood aerial image database with known ground truth has been used.</p> http://asp.eurasipjournals.com/content/2011/1/28
collection DOAJ
language English
format Article
sources DOAJ
author Stathaki Tania
Giannarou Stamatia
spellingShingle Stathaki Tania
Giannarou Stamatia
Optimal edge detection using multiple operators for image understanding
EURASIP Journal on Advances in Signal Processing
author_facet Stathaki Tania
Giannarou Stamatia
author_sort Stathaki Tania
title Optimal edge detection using multiple operators for image understanding
title_short Optimal edge detection using multiple operators for image understanding
title_full Optimal edge detection using multiple operators for image understanding
title_fullStr Optimal edge detection using multiple operators for image understanding
title_full_unstemmed Optimal edge detection using multiple operators for image understanding
title_sort optimal edge detection using multiple operators for image understanding
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2011-01-01
description <p>Abstract</p> <p>Extraction of features, such as edges for the understanding of aerial images, has been an important objective since the early days of remote sensing. This work aims at describing a new framework which allows for the quantitative combination of a preselected set of edge detectors based on the correspondence between their outcomes. This is inspired from the problem that despite the enormous amount of literature on edge detection techniques, there is no single technique that performs well in every possible image context. Two approaches are proposed for this purpose. The first approach is the well-known receiver operating characteristics analysis which is introduced for a sound quality evaluation of the edge maps estimated by combining different edge detectors. In the second approach, the so-called kappa statistics are employed in a novel fashion to amalgamate the above-mentioned selected edge maps to form an improved final edge image. This method is unique in the sense that the balance between the false detections (false positives and false negatives) is explicitly determined in advance and incorporated in the proposed method in a mathematical fashion. For the performance evaluation of the proposed techniques, a sample set of the RADIUS/DARPA-IU Fort Hood aerial image database with known ground truth has been used.</p>
url http://asp.eurasipjournals.com/content/2011/1/28
work_keys_str_mv AT stathakitania optimaledgedetectionusingmultipleoperatorsforimageunderstanding
AT giannaroustamatia optimaledgedetectionusingmultipleoperatorsforimageunderstanding
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