DocumentCode :
3285172
Title :
A Study on Geological Image Segmentation
Author :
Du Cheng ; Biao, Leng
Author_Institution :
Coll. of Electr. & Inf. Eng., Southwest Univ. for Nat. (swun), Chengdu, China
Volume :
3
fYear :
2009
fDate :
15-17 May 2009
Firstpage :
154
Lastpage :
157
Abstract :
As different geological different image, almost no exactly the same geological images, making the division of geological image has become very difficult. Of the current image processing technology, most algorithms are based on specific digital image analysis and cannot be used under any circumstances. There is almost none for the digital image processing algorithms to the tunnel headings; not to say what kind of image analysis and what kind of algorithms used for the specific tunnel heading digital image. This article is the study of geology through the digital images using HSI color model in the amount of similarity of the cluster, using the image error square and guidelines function C means clustering segmentation. Clustering in automatically, at the same time completed the labeling of objects and give full play to non-supervision of the advantages of clustering algorithm to image geological feature extraction, measurement and analysis and a higher level of understanding possible.
Keywords :
feature extraction; geology; geotechnical engineering; image colour analysis; image representation; image segmentation; pattern clustering; structural engineering computing; tunnels; C-means clustering segmentation; HSI color model; digital image analysis; digital image processing algorithm; feature extraction; geological image segmentation; tunnel heading digital image; Algorithm design and analysis; Clustering algorithms; Digital images; Geology; Guidelines; Image analysis; Image color analysis; Image processing; Image segmentation; Labeling; Image; Imagery processing; division;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology and Applications, 2009. IFITA '09. International Forum on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3600-2
Type :
conf
DOI :
10.1109/IFITA.2009.190
Filename :
5232083
Link To Document :
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