A Method to Derive Moment Invariants

Author

Wang Yuanbin ; Zhang Bin ; Yao Tianshun

Author_Institution

Inst. of Comput. Applic. Technol., Northeastern Univ., Shenyang, China

Volume

2

fYear

2009

fDate

11-12 April 2009

Firstpage

13

Lastpage

16

Abstract

Functions of moments that are invariant under geometric transformations are useful for image analysis and pattern recognition. The basic model of computer vision is projective transformation. Yet it is known that moment invariants for general projective transformations do not exist. This paper presents a novel method to derive moment invariants under restricted projective transformations. The form of the moment invariants is in a ratio of two determinants of moments. We first derive the relative moment invariants relating moments of the transformed image and moments of the original image. Then the absolute moment invariant is obtained by cancellation of the factors. The method is straightforward and extendible.

Keywords

computer vision; image recognition; matrix algebra; computer vision; geometric transformation; image analysis; matrix algebra; moment invariant method; pattern recognition; projective transformation; Automation; Computer applications; Computer vision; H infinity control; Image analysis; Jacobian matrices; Mechatronics; Pattern recognition; Polynomials; invariants; moments; pattern recognition; projective transformations;

fLanguage

English

Publisher

ieee

Conference_Titel

Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on

Conference_Location

Zhangjiajie, Hunan

Print_ISBN

978-0-7695-3583-8

Type

conf

DOI

10.1109/ICMTMA.2009.41

Filename

5203366