Edge Extraction Method Based on Separability of Image Features

Kazuhiro FUKUI

Edge Extraction Method Based on Separability of Image Features

Kazuhiro FUKUI

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This paper proposes a robust method for detecting step and ramp edges. In this method, an edge is defined not as a point where there is a large change in intensity, but as a region boundary based on the separability of image features which can be calculated by linear discriminant analysis. Based on this definition of an edge, its intensity can be obtained from the separability, which depends only on the shape of an edge. This characteristic enables easy selection of the optimum threshold value for the extraction of an edge, and this method can be applied to color and texture edge extraction. Experimental results have demonstrated that this proposed method is robust to noise and dulled edges, and, in addition, allows easy selection of the optimum threshold value.

Publication: IEICE TRANSACTIONS on Information Vol.E78-D No.12 pp.1533-1538

Publication Date: 1995/12/25

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Type of Manuscript: Special Section PAPER (Special Issue on Machine Vision Applications)

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Kazuhiro FUKUI, "Edge Extraction Method Based on Separability of Image Features" in IEICE TRANSACTIONS on Information, vol. E78-D, no. 12, pp. 1533-1538, December 1995, doi: .
Abstract: This paper proposes a robust method for detecting step and ramp edges. In this method, an edge is defined not as a point where there is a large change in intensity, but as a region boundary based on the separability of image features which can be calculated by linear discriminant analysis. Based on this definition of an edge, its intensity can be obtained from the separability, which depends only on the shape of an edge. This characteristic enables easy selection of the optimum threshold value for the extraction of an edge, and this method can be applied to color and texture edge extraction. Experimental results have demonstrated that this proposed method is robust to noise and dulled edges, and, in addition, allows easy selection of the optimum threshold value.
URL: https://globals.ieice.org/en_transactions/information/10.1587/e78-d_12_1533/_p

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@ARTICLE{e78-d_12_1533,
author={Kazuhiro FUKUI, },
journal={IEICE TRANSACTIONS on Information},
title={Edge Extraction Method Based on Separability of Image Features},
year={1995},
volume={E78-D},
number={12},
pages={1533-1538},
abstract={This paper proposes a robust method for detecting step and ramp edges. In this method, an edge is defined not as a point where there is a large change in intensity, but as a region boundary based on the separability of image features which can be calculated by linear discriminant analysis. Based on this definition of an edge, its intensity can be obtained from the separability, which depends only on the shape of an edge. This characteristic enables easy selection of the optimum threshold value for the extraction of an edge, and this method can be applied to color and texture edge extraction. Experimental results have demonstrated that this proposed method is robust to noise and dulled edges, and, in addition, allows easy selection of the optimum threshold value.},
keywords={},
doi={},
ISSN={},
month={December},}

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TY - JOUR
TI - Edge Extraction Method Based on Separability of Image Features
T2 - IEICE TRANSACTIONS on Information
SP - 1533
EP - 1538
AU - Kazuhiro FUKUI
PY - 1995
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E78-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 1995
AB - This paper proposes a robust method for detecting step and ramp edges. In this method, an edge is defined not as a point where there is a large change in intensity, but as a region boundary based on the separability of image features which can be calculated by linear discriminant analysis. Based on this definition of an edge, its intensity can be obtained from the separability, which depends only on the shape of an edge. This characteristic enables easy selection of the optimum threshold value for the extraction of an edge, and this method can be applied to color and texture edge extraction. Experimental results have demonstrated that this proposed method is robust to noise and dulled edges, and, in addition, allows easy selection of the optimum threshold value.
ER -