Generalized Invariant Moment Theory And Image Recognition

Zhan He; Ying Zhou; Zhen-pei Cheng

doi:10.1117/12.950281

2 March 1989 Generalized Invariant Moment Theory And Image Recognition

Zhan He, Ying Zhou, Zhen-pei Cheng

Proceedings Volume 1027, Image Processing II; (1989) https://doi.org/10.1117/12.950281
Event: 1988 International Congress on Optical Science and Engineering, 1988, Hamburg, Germany

Abstract

A new generalized invariant moment theory (GIMT) is presented in this paper. The fundamental ideas of GIMT are based on the concepts of generalized image moment and length-invariant under rotational transformation. The generalized invariant moments in this theory can be invariant under translation,scale and rotation and have definite significance. The relation between Hu's theory and the results of ours is discussed. We offer the generalized invariant moments of a simple figure and letter images with computer simulation and discuss the real-time extraction of generalized invarinat moments with a hybrid optical/digital system.

Citation Download Citation

Zhan He, Ying Zhou, and Zhen-pei Cheng "Generalized Invariant Moment Theory And Image Recognition", Proc. SPIE 1027, Image Processing II, (2 March 1989); https://doi.org/10.1117/12.950281

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