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Radial centroid curve for affine invariant features extraction
Yang J.1; Lan R.1; Tang Y.Y.2; Chen Y.1
2012-07-01
Source PublicationInternational Journal of Wavelets, Multiresolution and Information Processing
ISSN02196913
Volume10Issue:4
Abstract

The extraction of affine invariant features plays an important role in many fields of computer vision. Contour-based wavelet methods are unapplicable to objects with several separable components. In this paper, a method is proposed by converting the object into a closed curve, which is called radial centroid curve (RCC). Point on this curve is the centroid of radial line segment from centroid of the object. It is shown that the RCC derived from the affine transformed object is the same affine transformed version as that of the original object. An affine invariant function (AIF) is constructed by applying stationary wavelet transform (SWT) to the derived RCC. This scheme is applicable to objects with several separable components. Several experiments have been conducted to evaluate the performance of the proposed method. © 2012 World Scientific Publishing Company.

KeywordAffine Invariant Function Affine Transform Radial Centroid Curve Stationary Wavelet Transform
DOI10.1142/S021969131250035X
URLView the original
Language英語English
WOS IDWOS:000306592300005
Scopus ID2-s2.0-84864122502
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Citation statistics
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Nanjing University of Information Science and Technology
2.Chongqing University
Recommended Citation
GB/T 7714
Yang J.,Lan R.,Tang Y.Y.,et al. Radial centroid curve for affine invariant features extraction[J]. International Journal of Wavelets, Multiresolution and Information Processing, 2012, 10(4).
APA Yang J.., Lan R.., Tang Y.Y.., & Chen Y. (2012). Radial centroid curve for affine invariant features extraction. International Journal of Wavelets, Multiresolution and Information Processing, 10(4).
MLA Yang J.,et al."Radial centroid curve for affine invariant features extraction".International Journal of Wavelets, Multiresolution and Information Processing 10.4(2012).
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