On Image Analysis by the Methods of Moments

Authors:
Cho-Huak Teh;Roland T. Chin
Affiliations:
Univ. of Wisconsin, Madison;Univ. of Wisconsin, Madison
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1988

Citing 2
Cited 212

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Abstract

Various types of moments have been used to recognize image patterns in a number of applications. A number of moments are evaluated and some fundamental questions are addressed, such as image-representation ability, noise sensitivity, and information redundancy. Moments considered include regular moments, Legendre moments, Zernike moments, pseudo-Zernike moments, rotational moments, and complex moments. Properties of these moments are examined in detail and the interrelationships among them are discussed. Both theoretical and experimental results are presented.