JOURNAL ARTICLE

Robust Affine Invariant Region-Based Shape Descriptors: The ICA Zernike Moment Shape Descriptor and the Whitening Zernike Moment Shape Descriptor

Ye MeiD. Androutsos

Year: 2009 Journal:   IEEE Signal Processing Letters Vol: 16 (10)Pages: 877-880   Publisher: Institute of Electrical and Electronics Engineers

Abstract

In this letter, we proposed two new affine invariant region-based shape descriptors, the ICA Zernike moment shape descriptor (ICAZMSD) and the whitening Zernike moment shape descriptor (WZMSD). Either independent component analysis (ICA) or whitening, is first used to turn the original shape into a canonical form, in which the effects of scaling and skewing are eliminated. Next, the properties of the Zernike transform are used to further eliminate the effects of any possible rotation and reflection of the canonical shapes, in extracting the Zernike moments as the affine invariant region-based descriptors. Using the proposed ICAZMSD as shape feature, shape-based image retrieval experiments on a 4000 complex shape image database and on a 5600 simple shape image database, show retrieval rates of 99.80% and 92.25%, respectively. Using the proposed WZMSD as shape feature, the corresponding retrieval rates are 99.79% and 92.22%, respectively. The proposed WZMSD has almost equal performance to the proposed ICAZMSD, while having lower computational requirements.

Keywords:
Zernike polynomials Affine transformation Artificial intelligence Invariant (physics) Pattern recognition (psychology) Moment (physics) Mathematics Velocity Moments Feature extraction Shape analysis (program analysis) Computer vision Image retrieval Computer science Image (mathematics) Geometry Wavefront Optics Physics

Metrics

34
Cited By
4.34
FWCI (Field Weighted Citation Impact)
9
Refs
0.96
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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