Integrating quality in fuzzy reasoning edge detection

Author

Bombardier, Vincent ; Perez-oramas, Oliver ; Bremont, Jacques

Author_Institution

Equipe PRAISSIH, Nancy I Univ., France

Volume

1

fYear

2000

fDate

7-10 May 2000

Firstpage

313

Abstract

We describe an edge detection operator based on fuzzy linguistic rules. The aim of the work is to introduce “high level information” in low level image processing such as edge detection in order to adapt image processing to image context conditions so as to improve the detection. First, we present the fuzzy reasoning edge detection operator and secondly, we explain the two stages where we integrate information about image quality. We consider two ways of obtaining image quality either by expert assessment or by histogram analysis. The image quality information is used for choosing the most adapted homogeneity extraction function and modifying the membership functions of the operator

Keywords

Gaussian noise; edge detection; fuzzy logic; image segmentation; inference mechanisms; expert assessment; fuzzy linguistic rules; fuzzy reasoning edge detection; high level information; histogram analysis; homogeneity extraction function; image quality; low level image processing; membership functions; Convolution; Fuzzy logic; Fuzzy reasoning; Histograms; Image analysis; Image edge detection; Image processing; Image quality; Input variables; Machine vision;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on

Conference_Location

San Antonio, TX

ISSN

1098-7584

Print_ISBN

0-7803-5877-5

Type

conf

DOI

10.1109/FUZZY.2000.838678

Filename

838678