DocumentCode :
1968332
Title :
A Novel SVM for Crack Edge Checking of Coal CT Image
Author :
Lingfang, Sun ; Guocheng, Fang ; Wei, Meng
Author_Institution :
Sch. of Autom. Eng., Northeast Dianli Univ., Jilin, China
fYear :
2010
fDate :
30-31 Jan. 2010
Firstpage :
75
Lastpage :
78
Abstract :
After analyzing the characteristic of ICT (industrial computerized tomography) image and wavelet transformation singularity, an crack edge checking method for coal CT image based on SVM was studied and improved, and applied in crack edge checking of Coal CT image. First we get the direction and approximate bound of the crack using SVM, and then compare the average area grayscale to locate the crack area. At last, we adopt LS-SVM to detect the crack edge, which is processed using polynomial fit to get an accurate, continuous and independent crack edge image. The experiment of Coal CT image rotation validates the robustness of this algorithm, and the comparative experiments with other method prove that the algorithm has strong robustness against noise.
Keywords :
coal; computerised tomography; cracks; edge detection; polynomials; wavelet transforms; SVM; coal CT image; crack edge checking; industrial computerized tomography; polynomial fit; support vector machine; wavelet transformation singularity; Computed tomography; Image analysis; Image edge detection; Kernel; Noise robustness; Polynomials; Statistical learning; Support vector machine classification; Support vector machines; Underwater communication; CT image; Coal; Crack edge detection; Least squares support vector machines(LS-SVM);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing & Communication, 2010 Intl Conf on and Information Technology & Ocean Engineering, 2010 Asia-Pacific Conf on (CICC-ITOE)
Conference_Location :
Macao
Print_ISBN :
978-1-4244-5634-5
Electronic_ISBN :
978-1-4244-5635-2
Type :
conf
DOI :
10.1109/CICC-ITOE.2010.27
Filename :
5439268
Link To Document :
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