Orthogonal GF Moments for Image Representation

Author

Chen Wei ; Cai Zhanchuan ; Huang Jing

Author_Institution

Fac. of Inf. Technol., Macau Univ. of Sci. & Technol., Macau, China

fYear

2013

fDate

26-28 July 2013

Firstpage

278

Lastpage

280

Abstract

A new set of orthogonal moment functions named as GF moments (GFMs) was proposed in this paper. The kernel functions of GFMs is GF-system, which is a class of complete orthogonal spline function set of degree k(k=0,1,2,?). The implementation of GFMs does not involve any numerical approximation and has a rather low computation complexity, since the basis set has the advantages of lower order. These properties make GFMs superior to the traditional polynomial moments such as Legendre moments and Zernike moments, in terms of the image reconstruction. Our simulation results also show that GFMs have a better feature representation capability.

Keywords

computational complexity; image representation; set theory; splines (mathematics); GF-system; Legendre moments; Zernike moments; computation complexity; image reconstruction; image representation; kernel functions; numerical approximation; orthogonal GF moments; orthogonal moment functions; orthogonal spline function set; traditional polynomial moments; Image reconstruction; Kernel; Pattern recognition; Polynomials; Shape; Splines (mathematics); GF system; Image reconstruction; Moments; Orthogonal spline functions;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Graphics (ICIG), 2013 Seventh International Conference on

Conference_Location

Qingdao

Type

conf

DOI

10.1109/ICIG.2013.59

Filename

6643680