DocumentCode :
2003390
Title :
Hypercomplex moments application in invariant image recognition
Author :
Labunets, V.G. ; Labunets, E.V. ; Egiazarian, K. ; Astola, J.
Author_Institution :
Dept. of A&IT., Ural State Tech. Univ., Ekaterinburg, Russia
Volume :
2
fYear :
1998
fDate :
4-7 Oct 1998
Firstpage :
257
Abstract :
Moment invariants have found many applications in pattern recognition. The main difficulty in the application of moment invariants is their computation. The presented paper is devoted to elaboration of new methods of image invariant recognition in Euclidean and non-Euclidean 2-, 3 and n-dimensional spaces, based on the theory of Clifford hypercomplex numbers that allow to work out efficient algorithms. Algebraic invariant pattern recognition has been discussed in the literature, however the Clifford algebra based method allows a more elegant reformulation providing greater geometrical insight
Keywords :
algebra; image recognition; method of moments; Clifford algebra based method; Clifford hypercomplex numbers; Euclidean space; hypercomplex moments application; invariant image recognition; moment invariants; nonEuclidean 2-dimensional space; nonEuclidean 3-dimensional space; nonEuclidean n-dimensional space; Algebra; Biosensors; Computational geometry; Humans; Image recognition; Pattern recognition; Physics; Retina; Signal processing algorithms; Space technology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
0-8186-8821-1
Type :
conf
DOI :
10.1109/ICIP.1998.723359
Filename :
723359
Link To Document :
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