Classification of Rotated and Scaled Textured Images Using Invariants Based on Spectral Moments

Yasuo YOSHIDA; Yue WU

Classification of Rotated and Scaled Textured Images Using Invariants Based on Spectral Moments

Yasuo YOSHIDA, Yue WU

Full Text Views

0

Cite this

Summary :

This paper describes a classification method for rotated and scaled textured images using invariant parameters based on spectral-moments. Although it is well known that rotation invariants can be derived from moments of grey-level images, the use is limited to binary images because of its computational unstableness. In order to overcome this drawback, we use power spectrum instead of the grey levels to compute moments and adjust the integral region of moment evaluation to the change of scale. Rotation and scale invariants are obtained as the ratios of the different rotation invariants on the basis of a spectral-moment property with respect to scale. The effectiveness of the approach is illustrated through experiments on natural textures from the Brodatz album. In addition, the stability of the invariants with respect to the change of scale is discussed theoretically and confirmed experimentally.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E81-A No.8 pp.1661-1666

Publication Date: 1998/08/25

Publicized

Online ISSN

DOI

Type of Manuscript: Special Section PAPER (Special Section on Digital Signal Processing)

Category

Cite this

Copy

Yasuo YOSHIDA, Yue WU, "Classification of Rotated and Scaled Textured Images Using Invariants Based on Spectral Moments" in IEICE TRANSACTIONS on Fundamentals, vol. E81-A, no. 8, pp. 1661-1666, August 1998, doi: .
Abstract: This paper describes a classification method for rotated and scaled textured images using invariant parameters based on spectral-moments. Although it is well known that rotation invariants can be derived from moments of grey-level images, the use is limited to binary images because of its computational unstableness. In order to overcome this drawback, we use power spectrum instead of the grey levels to compute moments and adjust the integral region of moment evaluation to the change of scale. Rotation and scale invariants are obtained as the ratios of the different rotation invariants on the basis of a spectral-moment property with respect to scale. The effectiveness of the approach is illustrated through experiments on natural textures from the Brodatz album. In addition, the stability of the invariants with respect to the change of scale is discussed theoretically and confirmed experimentally.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e81-a_8_1661/_p

Copy

@ARTICLE{e81-a_8_1661,
author={Yasuo YOSHIDA, Yue WU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Classification of Rotated and Scaled Textured Images Using Invariants Based on Spectral Moments},
year={1998},
volume={E81-A},
number={8},
pages={1661-1666},
abstract={This paper describes a classification method for rotated and scaled textured images using invariant parameters based on spectral-moments. Although it is well known that rotation invariants can be derived from moments of grey-level images, the use is limited to binary images because of its computational unstableness. In order to overcome this drawback, we use power spectrum instead of the grey levels to compute moments and adjust the integral region of moment evaluation to the change of scale. Rotation and scale invariants are obtained as the ratios of the different rotation invariants on the basis of a spectral-moment property with respect to scale. The effectiveness of the approach is illustrated through experiments on natural textures from the Brodatz album. In addition, the stability of the invariants with respect to the change of scale is discussed theoretically and confirmed experimentally.},
keywords={},
doi={},
ISSN={},
month={August},}

Copy

TY - JOUR
TI - Classification of Rotated and Scaled Textured Images Using Invariants Based on Spectral Moments
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1661
EP - 1666
AU - Yasuo YOSHIDA
AU - Yue WU
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E81-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 1998
AB - This paper describes a classification method for rotated and scaled textured images using invariant parameters based on spectral-moments. Although it is well known that rotation invariants can be derived from moments of grey-level images, the use is limited to binary images because of its computational unstableness. In order to overcome this drawback, we use power spectrum instead of the grey levels to compute moments and adjust the integral region of moment evaluation to the change of scale. Rotation and scale invariants are obtained as the ratios of the different rotation invariants on the basis of a spectral-moment property with respect to scale. The effectiveness of the approach is illustrated through experiments on natural textures from the Brodatz album. In addition, the stability of the invariants with respect to the change of scale is discussed theoretically and confirmed experimentally.
ER -