JOURNAL ARTICLE

Robust affine invariant shape image retrieval using the ICA Zernike Moment Shape Descriptor

Abstract

In this paper, we proposed a new affine invariant region-based shape descriptor, the ICA Zernike Moment Shape Descriptor (ICAZMSD). IndependentComponent Analysis (ICA) 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 is 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 a 5600 simple shape image database, show promising retrieval rates of 99.80% and 92.25%, respectively.

Keywords:
Zernike polynomials Affine transformation Artificial intelligence Invariant (physics) Pattern recognition (psychology) Image retrieval Mathematics Affine shape adaptation Shape analysis (program analysis) Harris affine region detector Computer vision Feature extraction Velocity Moments Scaling Computer science Image (mathematics) Affine combination Geometry Wavefront Optics Physics

Metrics

9
Cited By
0.93
FWCI (Field Weighted Citation Impact)
7
Refs
0.81
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

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