Edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework

Conventional Canny edge detector can detect edges in image with additive noise effectively but not ultrasound image that are corrupted by multiplicative speckle noise which alleviates image resolution resulting in inaccurate characterization of object features. In this paper, we proposed to incorpor...

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Main Authors: Supriyanto, Eko, Chai, Humyan, Lai, Khin Wee
Format: Conference or Workshop Item
Published: 2011
Online Access:http://eprints.utm.my/id/eprint/45778/
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spelling my.utm.457782017-08-29T08:58:20Z http://eprints.utm.my/id/eprint/45778/ Edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework Supriyanto, Eko Chai, Humyan Lai, Khin Wee Conventional Canny edge detector can detect edges in image with additive noise effectively but not ultrasound image that are corrupted by multiplicative speckle noise which alleviates image resolution resulting in inaccurate characterization of object features. In this paper, we proposed to incorporate the modified SRAD into the Canny edge detector to replace the Gaussian blurring in the conventional Canny edge detector in order to suppress the multiplicative noise effectively while preserving the edge of the object in ultrasound image. The result shows that the proposed method can provide better result than conventional method in a much wider range of parameter values. The proposed method through experimental result indicates that it is capable of producing promising edge detection result in ultrasound image. 2011 Conference or Workshop Item PeerReviewed Supriyanto, Eko and Chai, Humyan and Lai, Khin Wee (2011) Edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework. In: The 15th Wseas Gscc Multiconference.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
description Conventional Canny edge detector can detect edges in image with additive noise effectively but not ultrasound image that are corrupted by multiplicative speckle noise which alleviates image resolution resulting in inaccurate characterization of object features. In this paper, we proposed to incorporate the modified SRAD into the Canny edge detector to replace the Gaussian blurring in the conventional Canny edge detector in order to suppress the multiplicative noise effectively while preserving the edge of the object in ultrasound image. The result shows that the proposed method can provide better result than conventional method in a much wider range of parameter values. The proposed method through experimental result indicates that it is capable of producing promising edge detection result in ultrasound image.
format Conference or Workshop Item
author Supriyanto, Eko
Chai, Humyan
Lai, Khin Wee
spellingShingle Supriyanto, Eko
Chai, Humyan
Lai, Khin Wee
Edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework
author_facet Supriyanto, Eko
Chai, Humyan
Lai, Khin Wee
author_sort Supriyanto, Eko
title Edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework
title_short Edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework
title_full Edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework
title_fullStr Edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework
title_full_unstemmed Edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework
title_sort edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework
publishDate 2011
url http://eprints.utm.my/id/eprint/45778/
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score 13.160551