Segmentation of Viscose Filament Fracture Surface Image Based on SOFM Network Fusion

Author

Zhang, Jiaquan ; Feng, Yi ; Lin, Xiaolong ; Zhang, Tieqiang ; Zhang, Weiyi

Author_Institution

Jilin Univ., Changchun, China

fYear

2010

fDate

25-26 Dec. 2010

Firstpage

1

Lastpage

3

Abstract

A method of viscose filament fracture surface image segmentation based on SOFM network fusion is proposed. Firstly, the binarization method based on two-way weighting sequential smooth is used to segment the two images which are obtained in different light intensity. Secondly, fuse the two binary images based on SOFM fusion. After that, the final segmentation image is obtained. Using this method can record the information of viscose filament fracture surface accurately. The experimental results show that this method is much better when we can´t get clear fiber images. At the same time, it provides a way to segment the ununiformity brightness images.

Keywords

fracture; image fusion; image segmentation; optical fibres; self-organising feature maps; viscosity; SOFM network fusion; SOFM neural network; binarization method; light intensity; two-way weighting sequential smooth; ununiformity brightness images; viscose filament fracture surface image segmentation; Artificial neural networks; Entropy; Fuses; Image segmentation; Optical fiber networks; Pixel; Surface cracks;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on

Conference_Location

Wuhan

ISSN

2156-7379

Print_ISBN

978-1-4244-7939-9

Electronic_ISBN

2156-7379

Type

conf

DOI

10.1109/ICIECS.2010.5678395

Filename

5678395