INVARIANT PATTERN RECOGNITION USING RIDGELET PACKETS AND THE FOURIER TRANSFORM

被引:10
作者
Chen, G. Y. [1 ]
Bhattacharya, P. [1 ]
机构
[1] Concordia Univ, Concordia Inst Informat Syst Engn, Montreal, PQ H3G 1M8, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Ridgelets; ridgelet packets; Fourier transform; pattern recognition; feature extraction; texture classification; TEXTURE CLASSIFICATION; MULTIRESOLUTION RECOGNITION; WAVELET TRANSFORM; ROTATION; FEATURES; DECOMPOSITION; REPRESENTATION; SEGMENTATION; DESCRIPTOR;
D O I
10.1142/S0219691309002854
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In this paper, we propose two novel invariant algorithms for pattern recognition by using ridgelet packets and the Fourier transform. Ridgelet packets provide many orthonormal bases that can effectively capture directional features present in pattern images. The Fourier transform is good at eliminating the orientation differences. By combining these two tools, very efficient rotation invariant pattern recognition techniques are created. Experimental results show that the proposed methods achieve very high classification rates and they outperform other state-of-the-art methods for rotation invariant pattern recognition under both noise-free and noisy environments.
引用
收藏
页码:215 / 228
页数:14
相关论文
共 40 条
[1]  
Brodatz P., 1966, Texture: A Photographic Album for Artists and Designers
[2]   An orthonormal-shell-Fourier descriptor for rapid matching of patterns in image database [J].
Bui, TD ;
Chen, GY ;
Feng, L .
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2001, 15 (08) :1213-1229
[3]  
Candes E.J., 1998, Ridgelets: Theory and Applications
[4]   Ridgelets:: a key to higher-dimensional intermittency? [J].
Candès, EJ ;
Donoho, DL .
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 1999, 357 (1760) :2495-2509
[5]   Ridgelets and the representation of mutilated Sobolev functions [J].
Candes, EJ .
SIAM JOURNAL ON MATHEMATICAL ANALYSIS, 2001, 33 (02) :347-368
[6]   Wavelet-based rotational invariant roughness features for texture classification and segmentation [J].
Charalampidis, D ;
Kasparis, T .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2002, 11 (08) :825-837
[7]   Rotation invariant pattern recognition using ridgelets, wavelet cycle-spinning and Fourier features [J].
Chen, GY ;
Bui, TD ;
Krzyzak, A .
PATTERN RECOGNITION, 2005, 38 (12) :2314-2322
[8]   Contour-based handwritten numeral recognition using multiwavelets and neural networks [J].
Chen, GY ;
Bui, TD ;
Krzyzak, A .
PATTERN RECOGNITION, 2003, 36 (07) :1597-1604
[9]   Invariant Fourier-wavelet descriptor for pattern recognition [J].
Chen, GY ;
Bui, TD .
PATTERN RECOGNITION, 1999, 32 (07) :1083-1088
[10]   ROTATION AND GRAY-SCALE TRANSFORM INVARIANT TEXTURE IDENTIFICATION USING WAVELET DECOMPOSITION AND HIDDEN MARKOV MODEL [J].
CHEN, JL ;
KUNDU, A .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1994, 16 (02) :208-214