Paper Info
Title
A Shape Representation Based On Polar Vector Fourier Descriptors
Abstract
Fourier descriptors (FDs) are the widely used shape descriptors. But FDs can only be used to objects with single boundary, and it is inapplicable to objects with several components. In this paper, a region-based method, which is called Polar Vector Fourier Descriptors (PVFDs), is developed to extract invariant features. Firstly, the Cartesian coordinate system is converted into polar coordinate system. Secondly, the original two-dimensional image is reshaped into a vector (which is called Polar Vector (PV)) by linking radial vector end-to-end along the polar angle. Then, PVFDs are derived by applying Fourier transformation to PV. Consequently, the derived PVFDs are invariant to scaling and rotation. Furthermore, it is applicable to objects with several components (such as some Chinese characters etc.). Experimental results show that the proposed method is superior to Hu's moments and complex moments (CMs).
Year
DOI
Venue
2016
10.1109/CIS.2016.122
PROCEEDINGS OF 2016 12TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS)
Keywords
Field
DocType
shape representation, polar vector, geometric invariance
Mathematical optimization,Mathematical analysis,Interpolation,Feature extraction,Polar coordinate system,Fourier transform,Polar,Invariant (mathematics),Geometry,Scaling,Mathematics,Cartesian coordinate system
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Jianwei Yang15812.73
Zhengda Lu200.34