Corner detection using morphological skeleton:an efficient and nonparametric approach

Dinesh, R. and Guru, D. S. (2006) Corner detection using morphological skeleton:an efficient and nonparametric approach. Computer vision - ACCV 2006, PT II, 3852. pp. 752-760. ISSN 978-3-540-32432-4

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Official URL: https://doi.org/10.1007/11612704_75

Abstract

In this paper we propose an effective and robust approach for detecting corner points on a given binary image. Unlike other corner detection methods the proposed method is non-parametric in nature, that is, it does not require any input parameter. The proposed method is based on mathematical morphology. It makes use of morphological skeleton for detecting corner points. Convex corner points are obtained by intersecting the morphological boundary and the corresponding skeleton, where as the concave corner points are obtained by intersecting the boundary and the skeleton of the complement image. Experimental results show that the proposed method is more robust and efficient in detecting corner points.

Item Type: Article
Subjects: D Physical Science > Computer Science
Divisions: Department of > Computer Science
Depositing User: LA manjunath user
Date Deposited: 28 Aug 2019 10:20
Last Modified: 11 Dec 2019 05:30
URI: http://eprints.uni-mysore.ac.in/id/eprint/7267

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