IEICE TRANSACTIONS on Information
Revision of Using Eigenvalues of Covariance Matrices in Boundary-Based Corner Detection
Summary :
In this paper, we present a revision of using eigenvalues of covariance matrices proposed by Tsai et al. as a measure of significance (i.e., curvature) for boundary-based corner detection. We first show the pitfall of Tsai et al.'s approach. We then further investigate the properties of eigenvalues of covariance matrices of three different types of curves and point out a mistake made by Tsai et al.'s method. Finally, we propose a modification of using eigenvalues as a measure of significance for corner detection to remedy their defect. The experiment results show that under the same conditions of the test patterns, in addition to correctly detecting all true corners, the spurious corners detected by Tsai et al.'s method disappear in our modified measure of significance.
- Publication
- IEICE TRANSACTIONS on Information Vol.E92-D No.9 pp.1692-1701
- Publication Date
- 2009/09/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E92.D.1692
- Type of Manuscript
- PAPER
- Category
- Pattern Recognition
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Keyword
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Wen-Bing HORNG, Chun-Wen CHEN, "Revision of Using Eigenvalues of Covariance Matrices in Boundary-Based Corner Detection" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 9, pp. 1692-1701, September 2009, doi: 10.1587/transinf.E92.D.1692.
Abstract: In this paper, we present a revision of using eigenvalues of covariance matrices proposed by Tsai et al. as a measure of significance (i.e., curvature) for boundary-based corner detection. We first show the pitfall of Tsai et al.'s approach. We then further investigate the properties of eigenvalues of covariance matrices of three different types of curves and point out a mistake made by Tsai et al.'s method. Finally, we propose a modification of using eigenvalues as a measure of significance for corner detection to remedy their defect. The experiment results show that under the same conditions of the test patterns, in addition to correctly detecting all true corners, the spurious corners detected by Tsai et al.'s method disappear in our modified measure of significance.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.1692/_p
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@ARTICLE{e92-d_9_1692,
author={Wen-Bing HORNG, Chun-Wen CHEN, },
journal={IEICE TRANSACTIONS on Information},
title={Revision of Using Eigenvalues of Covariance Matrices in Boundary-Based Corner Detection},
year={2009},
volume={E92-D},
number={9},
pages={1692-1701},
abstract={In this paper, we present a revision of using eigenvalues of covariance matrices proposed by Tsai et al. as a measure of significance (i.e., curvature) for boundary-based corner detection. We first show the pitfall of Tsai et al.'s approach. We then further investigate the properties of eigenvalues of covariance matrices of three different types of curves and point out a mistake made by Tsai et al.'s method. Finally, we propose a modification of using eigenvalues as a measure of significance for corner detection to remedy their defect. The experiment results show that under the same conditions of the test patterns, in addition to correctly detecting all true corners, the spurious corners detected by Tsai et al.'s method disappear in our modified measure of significance.},
keywords={},
doi={10.1587/transinf.E92.D.1692},
ISSN={1745-1361},
month={September},}
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TY - JOUR
TI - Revision of Using Eigenvalues of Covariance Matrices in Boundary-Based Corner Detection
T2 - IEICE TRANSACTIONS on Information
SP - 1692
EP - 1701
AU - Wen-Bing HORNG
AU - Chun-Wen CHEN
PY - 2009
DO - 10.1587/transinf.E92.D.1692
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2009
AB - In this paper, we present a revision of using eigenvalues of covariance matrices proposed by Tsai et al. as a measure of significance (i.e., curvature) for boundary-based corner detection. We first show the pitfall of Tsai et al.'s approach. We then further investigate the properties of eigenvalues of covariance matrices of three different types of curves and point out a mistake made by Tsai et al.'s method. Finally, we propose a modification of using eigenvalues as a measure of significance for corner detection to remedy their defect. The experiment results show that under the same conditions of the test patterns, in addition to correctly detecting all true corners, the spurious corners detected by Tsai et al.'s method disappear in our modified measure of significance.
ER -
English
