Journal ArticleDOI
Image analysis via the general theory of moments
TLDR
Two-dimensional image moments with respect to Zernike polynomials are defined, and it is shown how to construct an arbitrarily large number of independent, algebraic combinations of zernike moments that are invariant to image translation, orientation, and size as discussed by the authors.Abstract:
Two-dimensional image moments with respect to Zernike polynomials are defined, and it is shown how to construct an arbitrarily large number of independent, algebraic combinations of Zernike moments that are invariant to image translation, orientation, and size. This approach is contrasted with the usual method of moments. The general problem of two-dimensional pattern recognition and three-dimensional object recognition is discussed within this framework. A unique reconstruction of an image in either real space or Fourier space is given in terms of a finite number of moments. Examples of applications of the method are given. A coding scheme for image storage and retrieval is discussed.read more
Citations
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Journal ArticleDOI
Invariant image recognition by Zernike moments
Alireza Khotanzad,Y.H. Hong +1 more
TL;DR: A systematic reconstruction-based method for deciding the highest-order ZERNike moments required in a classification problem is developed and the superiority of Zernike moment features over regular moments and moment invariants was experimentally verified.
Journal ArticleDOI
Review of shape representation and description techniques
Dengsheng Zhang,Guojun Lu +1 more
TL;DR: This paper identifies some promising techniques for image retrieval according to standard principles and examines implementation procedures for each technique and discusses its advantages and disadvantages.
Journal ArticleDOI
On image analysis by the methods of moments
C.-H. Teh,Roland T. Chin +1 more
TL;DR: Various types of moments have been used to recognize image patterns in a number of applications and some fundamental questions are addressed, such as image-representation ability, noise sensitivity, and information redundancy.
Journal ArticleDOI
A survey of shape analysis techniques
TL;DR: This paper provides a review of shape analysis methods, which play an important role in systems for object recognition, matching, registration, and analysis.
Book
Feature Extraction and Image Processing
Mark S. Nixon,Alberto S. Aguado +1 more
TL;DR: The new edition of Feature Extraction and Image Processing provides an essential guide to the implementation of image processing and computer vision techniques, explaining techniques and fundamentals in a clear and concise manner, and features a companion website that includes worksheets, links to free software, Matlab files, solutions and new demonstrations.
References
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Journal ArticleDOI
Aircraft Identification by Moment Invariants
TL;DR: An experimental system is described in which certain features called moment invariants are extracted from binary television images and are used for automatic classification of aircraft types from optical images, exhibiting a significantly lower error rate than human observers.
Journal ArticleDOI
Phase retrieval from modulus data
TL;DR: In this paper, the phase retrieval of a complex signal f from its modulus |f| has been studied, where an additional constraint is imposed: knowledge of the modulus of F, the Fourier transform of f. The problems of noisy data and nonuniqueness are addressed.
Journal ArticleDOI
Wave-front analyzer using a maximum likelihood algorithm
TL;DR: In this paper, the pupil phase profile is obtained from the image irradiance or point spread function, which is then used to estimate the pupil's phase profile from point spread functions.
Journal ArticleDOI
Optical calculation of irradiance moments.
TL;DR: A scheme is described that uses optical processing techniques to obtain image irradiance moments of arbitrary order and the wave optical limitations on the attainable accuracies are discussed.
Journal ArticleDOI
On the uniqueness question in the problem of phase retrieval from intensity measurements
A. J. Devaney,R. Chidlaw +1 more
TL;DR: In this paper, the phase retrieval problem in geometrical optics is shown to possess a unique solution within the framework of the diffraction theory of image formation, and a simple proof and example of the nonuniqueness of phase retrieval in this limit is presented.