DocumentCode :
762518
Title :
Wavelet approximation-based affine invariant shape representation functions
Author :
Rube, Ibrahim Ei ; Ahmed, Maher ; Kamel, Mohamed
Author_Institution :
Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
Volume :
28
Issue :
2
fYear :
2006
Firstpage :
323
Lastpage :
327
Abstract :
In this paper, new wavelet-based affine invariant functions for shape representation are presented. Unlike the previous representation functions, only the approximation coefficients are used to obtain the proposed functions. One of the derived functions is computed by applying a single wavelet transform; the other function is calculated by applying two different wavelet transforms with two different wavelet families. One drawback of the previously derived detail-based invariant representation functions is that they are sensitive to noise at the finer scale levels, which limits the number of scale levels that can be used. The experimental results in this paper demonstrate that the proposed functions are more stable and less sensitive to noise than the detail-based functions.
Keywords :
approximation theory; image matching; image representation; wavelet transforms; affine invariant functions; approximation coefficients; shape representation; wavelet transforms; Cascading style sheets; Dynamic programming; Electric shock; Image segmentation; MPEG 7 Standard; Noise level; Noise shaping; Robust stability; Shape; Wavelet transforms; Index Terms- Wavelet transform; affine transformation; invariants.; shape representation; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2006.43
Filename :
1561190
Link To Document :
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