Paper Info
Title
Shape Feature Extraction Using Fourier Descriptors with Brightness in Content-Based Medical Image Retrieval
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.
Year
DOI
Venue
2008
10.1109/IIH-MSP.2008.16
IIH-MSP
Keywords
Field
DocType
fourier transforms,fourier descriptors,content-based medical image retrieval,standardized pixel brightness,fourier transform,shape feature vector,shape feature extraction,content-based medical image,contour-based shape feature extraction,fourier description,shape signature,feature extraction,better performance,image retrieval,overall performance,edge detection,brightness,fourier coefficient,boundary pixel,content-based retrieval,medical image processing,feature vector,pixel,shape,biomedical imaging,distance function
Computer vision,Pattern recognition,Computer science,Edge detection,Spectral signal-to-noise ratio,Short-time Fourier transform,Fourier transform,Feature extraction,Fourier series,Artificial intelligence,Discrete Fourier transform,Phase correlation
Conference
ISBN
Citations 
PageRank 
978-0-7695-3278-3
0
0.34
References 
Authors
8
5
Name
Order
Citations
PageRank
Gang Zhang100.34
Z. M. Ma260166.24
Qiang Tong3204.80
Ying He400.68
Tie-Nan Zhao520.69