PDE-based grain boundary detection

Author

Lu, Bibo ; Ning, Chao

Author_Institution

Sch. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China

Volume

2

fYear

2010

fDate

28-31 Aug. 2010

Firstpage

170

Lastpage

173

Abstract

A grain boundary detection method based on partial differential equation(PDE) is proposed. The whole scheme is improved by introducing two PDE image processing techniques: PDE-based image filtering and segmentation. The noise in microscope image is suppressed with a edge-preserving filter: total variation flow. The second contribution is an extension of level set to segment color microphotograph, where multichannel information is used to identify grains. Experimental results on real thin section image of andalusite demonstrate the performance of the proposed method.

Keywords

edge detection; filtering theory; image colour analysis; image denoising; image segmentation; microphotography; microscopes; partial differential equations; PDE image processing techniques; PDE-based grain boundary detection; PDE-based image filtering; PDE-based image segmentation; color microphotograph segmentation; edge preserving filter; grain identification; microscope image noise suppression; multichannel information; partial differential equation; real thin section andalusite image; total variation flow; Active contours; Grain boundaries; Image edge detection; Image segmentation; Level set; Noise; Smoothing methods; active contour; curve evolution; grain boundary detection; partial differential equation; total variation flow;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing (IITA-GRS), 2010 Second IITA International Conference on

Conference_Location

Qingdao

Print_ISBN

978-1-4244-8514-7

Type

conf

DOI

10.1109/IITA-GRS.2010.5602492

Filename

5602492