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Journal ArticleDOI

On the accuracy of Zernike moments for image analysis

TLDR
It is found that there is an inherent limitation in the precision of computing the Zernike moments due to the geometric nature of a circular domain.
Abstract
We give a detailed analysis of the accuracy of Zernike moments in terms of their discretization errors and the reconstruction power. It is found that there is an inherent limitation in the precision of computing the Zernike moments due to the geometric nature of a circular domain. This is explained by relating the accuracy issue to a celebrated problem in analytic number theory of evaluating the lattice points within a circle.

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Citations
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Journal ArticleDOI

Image analysis by Krawtchouk moments

TL;DR: It is shown that the Krawtchouk moments can be employed to extract local features of an image, unlike other orthogonal moments, which generally capture the global features.
Journal ArticleDOI

Efficient Dense-Field Copy–Move Forgery Detection

TL;DR: A new algorithm for the accurate detection and localization of copy-move forgeries, based on rotation-invariant features computed densely on the image, is proposed, using a fast approximate nearest-neighbor search algorithm, PatchMatch, especially suited for the computation of dense fields over images.
Journal ArticleDOI

Invariant image watermark using Zernike moments

TL;DR: A robust image watermark based on an invariant image feature vector using normalized Zernike moments of an image as the vector and is robust with respect to geometrical distortions and compression.
Journal ArticleDOI

Two-Dimensional Polar Harmonic Transforms for Invariant Image Representation

TL;DR: A set of 2D transforms, based on a set of orthogonal projection bases, to generate aSet of features which are invariant to rotation, called Polar Harmonic Transforms (PHTs), which encompass the orthogonality and invariance advantages of Zernike and pseudo-Zernike moments, but are free from their inherent limitations.
Journal ArticleDOI

Color Image Analysis by Quaternion-Type Moments

TL;DR: This paper provides a general formula of QTMs from which a set of quaternion-valued QTM invariants (QTMIs) are derived to image rotation, scale and translation transformations by eliminating the influence of transformation parameters.
References
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Journal ArticleDOI

Visual pattern recognition by moment invariants

TL;DR: It is shown that recognition of geometrical patterns and alphabetical characters independently of position, size and orientation can be accomplished and it is indicated that generalization is possible to include invariance with parallel projection.
Journal ArticleDOI

Image analysis via the general theory of moments

TL;DR: 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.
Journal ArticleDOI

Invariant image recognition by Zernike moments

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

On image analysis by the methods of moments

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

Feature extraction methods for character recognition--a survey

TL;DR: This paper presents an overview of feature extraction methods for off-line recognition of segmented (isolated) characters in terms of invariance properties, reconstructability and expected distortions and variability of the characters.
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