Image processing and classification of metal fracture surface

Author

Weng, Gui-rong

Author_Institution

Sch. of Mech. & Electr. Eng., Soochow Univ., Suzhou

Volume

1

fYear

2008

fDate

30-31 Aug. 2008

Firstpage

163

Lastpage

167

Abstract

In this paper, a method of the image processing of the metal fracture for eliminating the noise, detecting the edges of the image and classification of the typical morphology of the metal fracture surface by obtaining the imagespsila character based on the mathematical morphology will be described. The methods of the normalized pattern spectrum have unchangeable characteristic for rotating, zooming or moving the images. Then the images can be classified by using artificial neural network. In this paper, 60 images of corrosion fatigue fracture, stream design fracture and intergranular cracking fracture are used as a study samples and 48 images are used as a test samples. The data of the experiment explain the feasibility of the method and analyze the cause of the error.

Keywords

corrosion fatigue; edge detection; fatigue cracks; image classification; mechanical engineering computing; neural nets; artificial neural network; corrosion fatigue fracture; edges detection; image character; image classification; image processing; intergranular cracking fracture; mathematical morphology; metal fracture surface; normalized pattern spectrum; stream design fracture; Filters; Image analysis; Image processing; Pattern analysis; Pattern recognition; Shape measurement; Surface cracks; Surface morphology; Surface waves; Working environment noise; Metal Fracture Surface; Normalized Pattern Spectrum; Top-Hat Transformation; Typical Morphology;

fLanguage

English

Publisher

ieee

Conference_Titel

Wavelet Analysis and Pattern Recognition, 2008. ICWAPR '08. International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-2238-8

Electronic_ISBN

978-1-4244-2239-5

Type

conf

DOI

10.1109/ICWAPR.2008.4635769

Filename

4635769