Optimal Scale Edge Detection Utilizing Noise within Images

Edge detection techniques have common problems that include poor edge detection in low contrast images, speed of recognition and high computational cost. An efficient solution to the edge detection of objects in low to high contrast images is scale space analysis. However, this approach is time cons...

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Bibliographic Details
Main Author: Adnan Khashman
Format: Article
Language:English
Published: International Institute of Informatics and Cybernetics 2003-04-01
Series:Journal of Systemics, Cybernetics and Informatics
Subjects:
Online Access:http://www.iiisci.org/Journal/CV$/sci/pdfs/000017.pdf
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spelling doaj-02d31baeacf148e484b23028de3bcfcc2020-11-24T20:56:53ZengInternational Institute of Informatics and CyberneticsJournal of Systemics, Cybernetics and Informatics1690-45242003-04-01124650Optimal Scale Edge Detection Utilizing Noise within ImagesAdnan Khashman0 Electrical and Electronic Engineering Department, Near East University Edge detection techniques have common problems that include poor edge detection in low contrast images, speed of recognition and high computational cost. An efficient solution to the edge detection of objects in low to high contrast images is scale space analysis. However, this approach is time consuming and computationally expensive. These expenses can be marginally reduced if an optimal scale is found in scale space edge detection. This paper presents a new approach to detecting objects within images using noise within the images. The novel idea is based on selecting one optimal scale for the entire image at which scale space edge detection can be applied. The selection of an ideal scale is based on the hypothesis that "the optimal edge detection scale (ideal scale) depends on the noise within an image". This paper aims at providing the experimental evidence on the relationship between the optimal scale and the noise within images.http://www.iiisci.org/Journal/CV$/sci/pdfs/000017.pdf AEDSScale Space AnalysisNoise within ImagesOptimal ScaleEdge Detection
collection DOAJ
language English
format Article
sources DOAJ
author Adnan Khashman
spellingShingle Adnan Khashman
Optimal Scale Edge Detection Utilizing Noise within Images
Journal of Systemics, Cybernetics and Informatics
AEDS
Scale Space Analysis
Noise within Images
Optimal Scale
Edge Detection
author_facet Adnan Khashman
author_sort Adnan Khashman
title Optimal Scale Edge Detection Utilizing Noise within Images
title_short Optimal Scale Edge Detection Utilizing Noise within Images
title_full Optimal Scale Edge Detection Utilizing Noise within Images
title_fullStr Optimal Scale Edge Detection Utilizing Noise within Images
title_full_unstemmed Optimal Scale Edge Detection Utilizing Noise within Images
title_sort optimal scale edge detection utilizing noise within images
publisher International Institute of Informatics and Cybernetics
series Journal of Systemics, Cybernetics and Informatics
issn 1690-4524
publishDate 2003-04-01
description Edge detection techniques have common problems that include poor edge detection in low contrast images, speed of recognition and high computational cost. An efficient solution to the edge detection of objects in low to high contrast images is scale space analysis. However, this approach is time consuming and computationally expensive. These expenses can be marginally reduced if an optimal scale is found in scale space edge detection. This paper presents a new approach to detecting objects within images using noise within the images. The novel idea is based on selecting one optimal scale for the entire image at which scale space edge detection can be applied. The selection of an ideal scale is based on the hypothesis that "the optimal edge detection scale (ideal scale) depends on the noise within an image". This paper aims at providing the experimental evidence on the relationship between the optimal scale and the noise within images.
topic AEDS
Scale Space Analysis
Noise within Images
Optimal Scale
Edge Detection
url http://www.iiisci.org/Journal/CV$/sci/pdfs/000017.pdf
work_keys_str_mv AT adnankhashman optimalscaleedgedetectionutilizingnoisewithinimages
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