A new method for fast computation of moments based on 8-neighbor chain code applied to 2-D object recognition

Author

Ji, Guang-Rong ; Wang, Guo-Yu ; Houkes, Z. ; Zheng, Bing ; Han, Yan-ping

Author_Institution

Dept. of Electr. Eng., Ocean Univ. of Qingdao, China

Volume

2

fYear

1997

fDate

28-31 Oct 1997

Firstpage

974

Abstract

2D moment invariants have been successfully applied in pattern recognition tasks. The main difficulty of using moment invariants is the computational burden. To improve the algorithm of moments computation through an iterative method, an approach for fast computation of moments based on the 8-neighbor chain code is proposed in this paper. Then artificial neural networks are applied for 2D shape recognition with moment invariants. Compared with the method of polygonal approximation, this approach shows higher accuracy in shape representation and faster recognition speed in experiments

Keywords

image representation; method of moments; neural nets; object recognition; 2D moment invariants; 2D object recognition; 2D shape recognition; 8 neighbour chain code; artificial neural networks; computational burden; fast computation; iterative method; moment computation; pattern recognition; polygonal approximation; shape representation; two dimensional object recognition; Artificial neural networks; Image converters; Image recognition; Iterative algorithms; Iterative methods; Object recognition; Oceans; Pattern recognition; Shape; Two dimensional displays;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-4253-4

Type

conf

DOI

10.1109/ICIPS.1997.669116

Filename

669116