Standard

Hypercomplex moments application in invariant image recognition. / Labunets, V.; Labunets, Ekaterina V.; Egiazarian, Karen et al.
In: IEEE International Conference on Image Processing, Vol. 2, 1998, p. 257-261.

Research output: Contribution to journal › Conference article › peer-review

Harvard

Labunets, V, Labunets, EV, Egiazarian, K & Astola, JT 1998, 'Hypercomplex moments application in invariant image recognition', IEEE International Conference on Image Processing, vol. 2, pp. 257-261.

APA

Labunets, V., Labunets, E. V., Egiazarian, K., & Astola, J. T. (1998). Hypercomplex moments application in invariant image recognition. IEEE International Conference on Image Processing, 2, 257-261.

Vancouver

Labunets V, Labunets EV, Egiazarian K, Astola JT. Hypercomplex moments application in invariant image recognition. IEEE International Conference on Image Processing. 1998;2:257-261.

Author

Labunets, V. ; Labunets, Ekaterina V. ; Egiazarian, Karen et al. / Hypercomplex moments application in invariant image recognition. In: IEEE International Conference on Image Processing. 1998 ; Vol. 2. pp. 257-261.

BibTeX

@article{e39ea7ba655e44d2a908875c7ee5f3a2,
title = "Hypercomplex moments application in invariant image recognition",
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 have been discussed in the literature, however the Clifford algebra based method allows a more elegant reformulation providing greater geometrical insight.",
author = "V. Labunets and Labunets, {Ekaterina V.} and Karen Egiazarian and Astola, {Jaakko T.}",
year = "1998",
language = "English",
volume = "2",
pages = "257--261",
journal = "IEEE International Conference on Image Processing",
issn = "1522-4880",
publisher = "IEEE Computer Society",

}

RIS

TY - JOUR

T1 - Hypercomplex moments application in invariant image recognition

AU - Labunets, V.

AU - Labunets, Ekaterina V.

AU - Egiazarian, Karen

AU - Astola, Jaakko T.

PY - 1998

Y1 - 1998

N2 - 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 have been discussed in the literature, however the Clifford algebra based method allows a more elegant reformulation providing greater geometrical insight.

AB - 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 have been discussed in the literature, however the Clifford algebra based method allows a more elegant reformulation providing greater geometrical insight.

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=0032292212

M3 - Conference article

VL - 2

SP - 257

EP - 261

JO - IEEE International Conference on Image Processing

JF - IEEE International Conference on Image Processing

SN - 1522-4880

ER -

ID: 54139581