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Proceedings ArticleDOI

A comparative study of Fourier descriptors and Hu's seven moment invariants for image recognition

Qing Chen, +2 more
- Vol. 1, pp 103-106
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TLDR
Hu et al. as mentioned in this paper evaluated and compared the performance of Fourier descriptors and Hu's seven moment invariants for recognizing images with different spatial resolutions, including scale change, translation and rotation.
Abstract
The paper evaluates and compares the performance of Fourier descriptors and Hu's seven moment invariants for recognizing images with different spatial resolutions. Both Fourier descriptors and Hu's seven moment invariants have the preferred invariance property against image transformations, including scale change, translation and rotation. However, spatial resolution thresholds exist for both of them. In our experiment with the image recognition engine, for Fourier descriptors, with feature vectors composed by the first 10 elements of the series, the spatial resolution should not be less than 64/spl times/64 to achieve 100% recognition. For Hu's seven moment invariants, the minimum spatial resolution is 128/spl times/128.

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Citations
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Proceedings ArticleDOI

Analysis of Hu's moment invariants on image scaling and rotation

TL;DR: An analysis with respect to the variation of moment invariants on image geometric transformation is presented, so as to analyze the effect of image's scaling and rotation.
Journal ArticleDOI

Image analysis by discrete orthogonal Racah moments

TL;DR: A new set of discrete orthogonal moments is proposed, based on the discrete Racah polynomials, which eliminate the need for numerical approximations and demonstrate Racah moments' feature representation capability by means of image reconstruction and compression.
Journal ArticleDOI

Image analysis by discrete orthogonal dual Hahn moments

TL;DR: The proposed dual Hahn moments perform better than the Legendre moments, Tchebichef moments, and Krawtchouk moments in terms of image reconstruction capability in both noise-free and noisy conditions.
Journal ArticleDOI

Automatic surface defect detection for mobile phone screen glass based on machine vision

TL;DR: An improved fuzzy c-means cluster (IFCM) algorithm is developed, and the proposed algorithms are validated using a number of experimental tests on MPSG images, showing that it has better performance than other methods.
Book ChapterDOI

Image analysis by discrete orthogonal hahn moments

TL;DR: A new set of discrete orthogonal polynomials, namely Hahn polynmials, are introduced and the related Hahn moment functions defined on this orthosomatic basis set are investigated and applied to image reconstruction.
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

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

Three-dimensional shape analysis using moments and Fourier descriptors

TL;DR: A procedure for using moment-based feature vectors to identify a three-dimensional object from a two-dimensional image recorded at an arbitrary viewing angle and range is presented and a moment form called standard moments is considered, rather than the usual moment invariants.
Book

Recognizing Planar Objects Using Invariant Image Features

TL;DR: Translation, rotation, scale and contrast invariants, algebraic and projective invariant, and recognition of partially occluded objects are summarized.
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