DocumentCode :
2846219
Title :
An Efficient Sub-Pixel Edge Extraction Method for CT Brain Images
Author :
Cao, Ying ; Wang, Beilei ; Xiao, Huiming ; Jiang, Huiyan ; Zhu, Zhiliang ; Yin, Quanjun
Author_Institution :
Multimedia Med. Inf. Technol. Lab., Northeastern Univ. Shenyang, Shenyang, China
fYear :
2009
fDate :
11-13 Dec. 2009
Firstpage :
1
Lastpage :
4
Abstract :
An efficient sub-pixel level edge detection algorithm for CT brain images is presented in this paper, which is based on Sobel operator, Zernike moments operator, and derived limited non-optimum suppression (LNOS) scheme. Sobel operator is firstly used to extract potential edge points in pixel level, and then Zernike moments operator, together with derived limited non-optimum suppression approach, is utilized to relocate the edges to sub-pixel level. The experiments on CT brain images are conducted to validate the usage of Sobel operator for pixel-level edge operator, and demonstrate that the proposed method is efficient to achieve sub-pixel edge detection for CT brain images, which tends to locate edges more accurately and preserve desired texture details.
Keywords :
Zernike polynomials; brain; computerised tomography; edge detection; feature extraction; medical image processing; CT brain image; Sobel operator; Zernike moments operator; limited nonoptimum suppression; pixel-level edge operator; subpixel level edge extraction; Biomedical imaging; Brain; Computed tomography; Convolution; Data mining; Image edge detection; Information technology; Laboratories; Moment methods; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
Type :
conf
DOI :
10.1109/CISE.2009.5365089
Filename :
5365089
Link To Document :
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