Corner characterization by statistical analysis of gradient-direction

Author

Yin, Shi ; Balchen, Jens G.

Author_Institution

Dept. of Mech. & Ind. Eng., Toronto Univ., Ont., Canada

Volume

2

fYear

1997

fDate

26-29 Oct 1997

Firstpage

760

Abstract

A new approach to grey-level image corner characterization is proposed in this paper which is based on the statistical analysis of the gradient-direction in an intensity image, and takes the signal to noise ratio (SNR) into account. The proposed approach can detect corner structure, the number of lines and their orientations which construct the corner; as well as the corner location (intersection point of the lines) in subpixel accuracy. Experiments on both synthetic and real images reveal that the proposed approach can cope well with image noise

Keywords

edge detection; optical noise; statistical analysis; accuracy; corner characterization; corner location; corner structure; gradient-direction; image noise; intensity image; intersection point; line numbers; orientations; real images reveal; signal to noise ratio; statistical analysis; synthetic images; Application software; Computer vision; Cybernetics; Histograms; Image edge detection; Industrial engineering; Machine vision; Shape; Signal to noise ratio; Statistical analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1997. Proceedings., International Conference on

Conference_Location

Santa Barbara, CA

Print_ISBN

0-8186-8183-7

Type

conf

DOI

10.1109/ICIP.1997.638607

Filename

638607