DocumentCode
2644713
Title
Shape Feature Extraction Using Fourier Descriptors with Brightness in Content-Based Medical Image Retrieval
Author
Zhang, Gang ; Ma, Z.M. ; Tong, Qiang ; He, Ying ; Zhao, Tienan
Author_Institution
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang
fYear
2008
fDate
15-17 Aug. 2008
Firstpage
71
Lastpage
74
Abstract
Contour-based shape feature extraction is one of the important research contents in content-based medical image retrieval. The paper presents a method using Fourier descriptors with brightness. The method uses centroid distance function to compute shape signature from boundary pixels of a shape. Fourier transform is used for shape signature to compute Fourier coefficients, and standardized pixel brightness is introduced into computational process of the Fourier coefficients. The Fourier coefficients which are invariant to translation, scaling, rotation and change of start point are used as Fourier descriptors. And shape feature vector consists of the Fourier descriptors. Experiments show that the system which uses the method in the paper has better performance than that which used Fourier descriptions in terms of overall performance.
Keywords
Fourier transforms; content-based retrieval; edge detection; feature extraction; image retrieval; medical image processing; Fourier descriptors; Fourier transform; brightness; content-based medical image retrieval; contour-based shape feature extraction; shape feature vector; shape signature; Biomedical imaging; Brightness; Content based retrieval; Data mining; Feature extraction; Fourier transforms; Image retrieval; Information retrieval; Shape; Signal processing; Content-based Medical Image Retrieval; Fourier Descriptors; shape feature extraction;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Hiding and Multimedia Signal Processing, 2008. IIHMSP '08 International Conference on
Conference_Location
Harbin
Print_ISBN
978-0-7695-3278-3
Type
conf
DOI
10.1109/IIH-MSP.2008.16
Filename
4604010
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