Fuzzy convergence

Author

Hoover, Adam ; Goldbaum, Michael

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA

fYear

1998

fDate

23-25 Jun 1998

Firstpage

716

Lastpage

721

Abstract

This work considers the problem of discovering areas of convergence of line-like shapes in an image. The motivating application is to use the convergence of the blood vessel network to automatically locate the optic nerve in an ocular fundus image. A fuzzy segment model is proposed, based on a conjecture that line-like shapes only contribute to a perception of convergence in their near neighborhood. Using this model, a voting-type method is described to compute a convergence image, which can be searched for one absolute, or one or more relative, strongest points of convergence. Results are presented for twenty ocular fundus images, with a 65% success rate for finding the optic nerve

Keywords

convergence of numerical methods; fuzzy logic; image segmentation; areas of convergence; blood vessel network; fuzzy convergence; fuzzy segment model; line-like shapes; ocular fundus image; optic nerve; voting-type method; Application software; Biomedical imaging; Biomedical optical imaging; Blood vessels; Convergence; Image converters; Image segmentation; Optical fiber networks; Pixel; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on

Conference_Location

Santa Barbara, CA

ISSN

1063-6919

Print_ISBN

0-8186-8497-6

Type

conf

DOI

10.1109/CVPR.1998.698682

Filename

698682