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A New Edge Detector Using 2D Beta Distribution

A New Edge Detector Using 2D Beta Distribution
A New Edge Detector Using 2D Beta Distribution
Edge detection is a problem of fundamental importance in image analysis. In typical images, edges characterize object boundaries and are therefore useful for segmentation, registration, feature extraction, and identification of objects in a scene. Edge detection is traditionally implemented by convolving the image with masks. These masks are constructed using a first or second derivative operators. Thus, the problem of edge detection is therefore related to the problem of mask construction. Gaussian distribution has been used to build masks for the first and second derivative. However, this distribution has limitation in its shape, it has only symmetric shape. Gaussian distribution is a private case of Beta distribution. In the paper we will use the Beta distribution to construct the masks and then detection the edge of objects in images. The constructed masks are applied to images and we obtained good results.
Al-Owaisheq, E.
cade88ec-30c8-4ebb-b29a-c7afd4678bdd
Al-Owisheq, A.
e7624792-8ddd-4b3d-9b45-655c48003543
El-Zaart, A.
6ca6b62c-1ad3-46ef-aa30-53c3e4459e14
Al-Owaisheq, E.
cade88ec-30c8-4ebb-b29a-c7afd4678bdd
Al-Owisheq, A.
e7624792-8ddd-4b3d-9b45-655c48003543
El-Zaart, A.
6ca6b62c-1ad3-46ef-aa30-53c3e4459e14

Al-Owaisheq, E., Al-Owisheq, A. and El-Zaart, A. (2008) A New Edge Detector Using 2D Beta Distribution. 3rd International Conference on Information and Communication Technologies: From Theory to Applications (ICTTA 2008)., Damascus, Syrian Arab Republic. 07 - 11 Apr 2008. (doi:10.1109/ICTTA.2008.4530134).

Record type: Conference or Workshop Item (Paper)

Abstract

Edge detection is a problem of fundamental importance in image analysis. In typical images, edges characterize object boundaries and are therefore useful for segmentation, registration, feature extraction, and identification of objects in a scene. Edge detection is traditionally implemented by convolving the image with masks. These masks are constructed using a first or second derivative operators. Thus, the problem of edge detection is therefore related to the problem of mask construction. Gaussian distribution has been used to build masks for the first and second derivative. However, this distribution has limitation in its shape, it has only symmetric shape. Gaussian distribution is a private case of Beta distribution. In the paper we will use the Beta distribution to construct the masks and then detection the edge of objects in images. The constructed masks are applied to images and we obtained good results.

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More information

Published date: 2008
Venue - Dates: 3rd International Conference on Information and Communication Technologies: From Theory to Applications (ICTTA 2008)., Damascus, Syrian Arab Republic, 2008-04-07 - 2008-04-11
Organisations: Web & Internet Science

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Local EPrints ID: 266927
URI: http://eprints.soton.ac.uk/id/eprint/266927
PURE UUID: f573b04f-02f6-4561-a328-0ed15d75684b

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Date deposited: 20 Nov 2008 12:56
Last modified: 14 Mar 2024 08:38

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Contributors

Author: E. Al-Owaisheq
Author: A. Al-Owisheq
Author: A. El-Zaart

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