|
|
|
Status of pattern recognition with wavelet analysis |
| Tang Yuanyan |
| College of Computer Science, Chongqing University; Department of Computer Science, Hong Kong Baptist University; |
|
|
|
|
Abstract Pattern recognition has become one of the fastest growing research topics in the fields of computer science and electrical and electronic engineering in the recent years. Advanced research and development in pattern recognition have found numerous applications in such areas as artificial intelligence, information security, biometrics, military science and technology, finance and economics, weather forecast, image processing, communication, biomedical engineering, document processing, robot vision, transportation, and endless other areas, with many encouraging results. The achievement of pattern recognition is most likely to benefit from some new developments of theoretical mathematics including wavelet analysis. This paper aims at a brief survey of pattern recognition with the wavelet theory. It contains the following respects: analysis and detection of singularities with wavelets; wavelet descriptors for shapes of the objects; invariant representation of patterns; handwritten and printed character recognition; texture analysis and classification; image indexing and retrieval; classification and clustering; document analysis with wavelets; iris pattern recognition; face recognition using wavelet transform; hand gestures classification; character processing with B-spline wavelet transform; wavelet-based image fusion, and others.
|
|
Issue Date: 05 September 2008
|
|
| 1 |
Auslander L, Kailath T, Mitter S, eds. Signal Processing I: Signal Processing Theory. New York: Springer-Verlag, 1990
|
| 2 |
Beylkin G, Coifman R, Daubechies I, et al.. Wavelets and their Applications. MA: Jones and Bartlett, 1991
|
| 3 |
Chui C K . An Introduction to Wavelets. Boston: Academic Press, 1992
|
| 4 |
Daubechies I . Wavelettransform, time-frequency localization and signal analysis. IEEE Transactions Information Theory, 1990, 36: 961–1005.
doi:10.1109/18.57199
|
| 5 |
Grossmann A, Morlet J . Decomposition of hardy functioninto square integrable wavelets of constant shape. SIAM J. Math. Anal., 1984, 15: 723–736.
doi:10.1137/0515056
|
| 6 |
IEEE. Special issueon wavelets and signal processing. IEEETransactions on Signal Processing, 1993, 41(12): 3213–3600
|
| 7 |
Mallat S . Atheory of multiresolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern Analysis and MachineIntelligence, 1989, 11: 674–693.
doi:10.1109/34.192463
|
| 8 |
Meyer Y . Ondeletteset Fonctions Splines: Seminaire EDP. EcolePolytechnique, Paris, 1986
|
| 9 |
SPIE. Special issueon wavelet applications. In: Harold H.Szu, editor, Proceedings of SPIE 2242, 1994
|
| 10 |
Chen C H, Lee J S, Sun Y N . Wavelet transformation for gray-level corner detection. Pattern Recognition, 1995, 28(6): 853–861.
doi:10.1016/0031‐3203(94)00169‐M
|
| 11 |
Chen G, Yang Y H, Edge detection by regularizedcubic B-spline fitting. IEEE Transactionson Systems, Man and Cybernetics, April, 1995, 25(4): 636–643.
doi:10.1109/21.370194
|
| 12 |
Chuang G C H, Kuo C C J . Wavelet descriptor of planarcurves: theory and applications”. IEEE Transactions Image Processing, 1996, 5(1): 56–70.
doi:10.1109/83.481671
|
| 13 |
Deng W A, Lyengar S S . A new probability relaxationscheme and its application to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996, 18(4): 432–443.
doi:10.1109/34.491624
|
| 14 |
Law T, Iton H, Seki H . Image filtering, edge detection, and edge tracing usingfuzzy reasoning. IEEE Transactions on PatternAnalysis and Machine Intelligence, 1996, 18(5): 481–491.
doi:10.1109/34.494638
|
| 15 |
Mallat S, Hwang W L . Singularity detection andprocessing with wavelets. IEEE Transactionson Information Theory, 1992, 38: 617–643.
doi:10.1109/18.119727
|
| 16 |
Tang Y Y, Yang L H, Feng L . Contour detection of handwriting by modular-angle-separatedwavelets. In: Proc. of the 6-th Inter.Workshop on Frontiers of Handwriting Recognition (IWFHR-VI), Taejon, Korea, August 1998, 357–366
|
| 17 |
Tang Y Y, Yang L H, Liu J . Wavelet-based edge detection in Chinese document. In: Proc. the 17th Int. Conf. on Computer Processingof Oriental Languages, 1997, volume 1, 333–336
|
| 18 |
Thune M, Olstad B, Thune N . Edge detection in noisy data using finite mixture distributeanalysis. Pattern Recognition, 1997, 30(5): 685–699.
doi:10.1016/S0031‐3203(96)00115‐X
|
| 19 |
Tieng Q M, Boles W W . Recognition of 2D objectcontours using the wavelet transform zero-crossing representation. IEEE Transactions on Pattern Analysis and MachineIntelligence, 1997, 19: 910–916.
doi:10.1109/34.608294
|
| 20 |
Young R K . Wavelet Theory and its Applications. Boston: Kluwer Academic Publishers, 1993
|
| 21 |
Tang Y Y, Li B F, Ma H, et al.. Ring-projection-wavelet-fractal signatures:a novel approach to feature extraction”. IEEE Transactions on Circuits and Systems II, 1998, 45(8): 1130–1134.
doi:10.1109/82.718824
|
| 22 |
Tang Y Y, Liu J M, Ma H, et al.. Wavelet orthonormal decomposition for extractingfeatures in pattern recognition. InternationalJournal of Pattern Recognition and Artificial Intelligence, 1999, 13(6): 803–831.
doi:10.1142/S0218001499000458
|
| 23 |
Tieng Q M, Boles W W . Wavelet-based affine invariantrepresentation: a tool for recognizing planar objects in 3D space. IEEE Transactions on Pattern Analysis and MachineIntelligence, 1997, 19: 846–857.
doi:10.1109/34.608288
|
| 24 |
Wunsch P, Laine A F . Wavelet descriptors for multiresolutionrecognition of handprinted characters. Pattern Recognition, 1995, 28(8): 1237–1249.
doi:10.1016/0031‐3203(95)00001‐G
|
| 25 |
Haley G M, Manjunath B S . Rotation-invariant textureclassification using a complete space-frequency model”. IEEE Transactions on Image Processing, 1999, 8(2): 255–269.
doi:10.1109/83.743859
|
| 26 |
Shen D, Ip Horace H S . Discriminative wavelet shapedescriptors for recognition of 2D pattern. Pattern Recognition, 1999, 32: 151–165.
doi:10.1016/S0031‐3203(98)00137‐X
|
| 27 |
Yoon S H, Kim J H, Alexander W E, et al.. An optimum solution for scale-invariant objectrecognition based on the multi-resolution approximation. Pattern Recognition, 1998, 31: 889–908.
doi:10.1016/S0031‐3203(97)00111‐8
|
| 28 |
Kunte R S, Samuel R D S . Wavelet descriptors for recognitionof basic symbols in printed Kannada text. International Journal of Wavelets, Multiresolution and InformationProcessing, 2007, 5(2): 351–367.
doi:10.1142/S0219691307001793
|
| 29 |
Lee S W, Kim C H, Ma H, et al.. Multiresolution recognition of unconstrainedhandwritten numerals with wavelet transform and multilayer clusterneural network. Pattern Recognition, 1996, 29: 1953–1961.
doi:10.1016/S0031‐3203(96)00053‐2
|
| 30 |
Tang Y Y, Ma H, Li B, et al.. Character recognition based on doubechies wavelet. In: Proceedings of The First Int. Conf. on MultimodelInterface (ICMI'96), Beijing: Tsinghua University Press, 1996, 215–220
|
| 31 |
Van de Wouwer G, Schenuders P, Van Dyck D . Statistical texture characterization from discrete waveletrepresentation. IEEE Transactions on ImageProcessing, 1999, 8: 592–598.
doi:10.1109/83.753747
|
| 32 |
Van de Wouwer G, Scheunders P, Livens S, et al.. Wavelet correlation signatures for color texturecharacterization”. Pattern Recognition, 1999, 32: 443–451.
doi:10.1016/S0031‐3203(98)00035‐1
|
| 33 |
Liang K H, Tjahjadi T . Adaptive scale fixing formultiscale texture segmentation. IEEE Transactionson Image Processing, 2006, 15(1): 249–256.
doi:10.1109/TIP.2005.860340
|
| 34 |
Muneeswaran K, Ganesan L, Arumugam S, et al.. A novel approach combing Gabor wavelet transformsand moments for texture segmentation. InternationalJournal of Wavelets, Multiresolution and Information Processing, 2005, 3(4): 559–572.
doi:10.1142/S0219691305001020
|
| 35 |
Jain P, Merchant S N . Wavelet-based multiresolutionhistogram for fast image retrieval. InternationalJournal of Wavelets, Multiresolution and Information Processing, 2004, 2(1): 59–73.
doi:10.1142/S0219691304000354
|
| 36 |
Ksantini R, Ziou D, Dubeau F, et al.. Image retrieval based on region separation andmultiresolution analysis. InternationalJournal of Wavelets, Multiresolution and Information Processing, 2006, 4(1): 147–175.
doi:10.1142/S0219691306001142
|
| 37 |
Kubo M, Aghbari Z, Makinouchi A . Content-based image retrieval technique using wavelet-basedshift and brightness invariant edge feature. International Journal of Wavelets, Multiresolution and InformationProcessing, 2003, 1(2): 163–178.
doi:10.1142/S0219691303000141
|
| 38 |
Moghaddam H A, Khajoie TT, Rouhi A H, et al.. Wavelet correlogram: a new approach for imageindexing and retrieval. Pattern Recognition., 2005, 38(12): 2506–2518.
doi:10.1016/j.patcog.2005.05.010
|
| 39 |
Special Issue on Digital Library. IEEE Transactions on Pattern Analysis And Machine Intelligence, 18, 1996
|
| 40 |
Smeulders A W M, Worring M, Santini S, et al.. Content-based image retrieval at the end ofearly years”. IEEE Transactions onPattern Analysis and Machine Intelligence, 2000, 22: 1349–13805.
doi:10.1109/34.895972
|
| 41 |
Murtagh F Starck J L . Pattern clustering basedon noise modeling in wavelet space. PatternRecognition, 1998, 31: 847–855.
doi:10.1016/S0031‐3203(97)00115‐5
|
| 42 |
Shankar B U, Meher S K, AChosh. Neuro-wavelet classifier for multispectral remote sensingimages. International Journal of Wavelets,Multiresolution and Information Processing, 2007, 5(4): 589–611.
doi:10.1142/S0219691307001914
|
| 43 |
Tang Y Y, Yang LH, Liu J M, et al.. Wavelet Theory and Its Applications to PatternRecognition. Singapore: World Scientific Publishing Co. Pte, Ltd., 2000
|
| 44 |
Liang K H, Chang F, Tan T M, et al.. Multiresolution hadamard representation andits application to document image analysis. In: Proceedingsof The Second Int. Conf. on Multimodel Interface (ICMI'99), Hong Kong, January 5–7 1999, V1–6
|
| 45 |
Tang Y Y, Liu J, Ma H, et al.. Two-dimensional wavelet transform in documentanalysis. In: Proceedings of The FirstInt. Conf. on Multimodel Interface (ICMI'96). Beijing: Tsinghua University Press, 1996, 274–279
|
| 46 |
Tang Y Y, Ma H, Liu J M, et al.. Multiresolution analysis in extraction of referencelines from documents with graylevel background. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19: 921–926.
doi:10.1109/34.608296
|
| 47 |
Tang Y Y, Ma H, Xi D H, et al.. Extraction of reference lines from documentwith grey-level background using sub-image of wavelets.In: Proceedings of the 3rd International Conferenceon Document Analysis and Recognition, Montreal, Canada, Oct. 14–16 1995, 571–574
|
| 48 |
Daugman J . Demodulationby complex-valued wavelets for stochastic pattern recognition. International Journal of Wavelets, Multiresolutionand Information Processing, 2003, 1(1): 1–317.
doi:10.1142/S0219691303000025
|
| 49 |
Kouzani A Z, Ong S H . Lighting-effects classificationin facial images using wavelet packets transform. International Journal of Wavelets, Multiresolution and InformationProcessing, 2003, 1(2): 199–215.
doi:10.1142/S021969130300013X
|
| 50 |
Lai J H, Yuen P C, Feng G C . Spectroface: a Fourier-based approach for human facerecognition. In: Proceedings of The SecondInt. Conf. on Multimodel Interface (ICMI'99), 1999, VI115–120
|
| 51 |
Yang L H, Bui T D, Suen C Y . Image recognition based on nonlinear wavelet approximation. International Journal of Wavelets, Multiresolutionand Information Processing, 2003, 1(2): 151–161.
doi:10.1142/S0219691303000104
|
| 52 |
Kumar S, Kumar D K . Visual hand gestures classificationusing wavelet transforms and moment based features. International Journal of Wavelets, Multiresolution and InformationProcessing, 2005, 3(1): 79–101.
doi:10.1142/S0219691305000762
|
| 53 |
Kumar S, Kumar D K, Sharma A, et al.. Visual hand gestures classification using wavelettransforms. International Journal of Wavelets,Multiresolution and Information Processing, 2003, 1(4): 373–392.
doi:10.1142/S0219691303000232
|
| 54 |
Sharnia A, Kumart D K, Kumar S . Wavelet directional histograms of the spatio-temporaltemplates of human gestures. InternationalJournal of Wavelets, Multiresolution and Information Processing, 2004, 2(3): 283–298.
doi:10.1142/S0219691304000512
|
| 55 |
Yang F, Wang Z, Yu Y L . Chinese typeface generation and composition using B-splinewavelet transform. In: Proceedings ofSPIE, Wavelet Applications V Orlando, Florida, 1998, 616–620
|
| 56 |
El-Khamy S E, Hadhoud M M, Dessouky M I, et al.. Wavelet fusion: a tool to break the limits onLMMSE image super-resolution. InternationalJournal of Wavelets, Multiresolution and Information Processing, 2006, 4(1): 105–118.
doi:10.1142/S0219691306001129
|
| 57 |
Li H . Wavelet-basedweighted average and human vision system image fusion. International Journal of Wavelets, Multiresolution and InformationProcessing, 2006, 4(1): 97–103.
doi:10.1142/S0219691306001117
|
| 58 |
Li S . Multisensorremote sensing image fusion using stationary wavelet transform: effectsof basis and decomposition level. InternationalJournal of Wavelets, Multiresolution and Information Processing, 2008, 6(1): 37–50.
doi:10.1142/S0219691308002203
|
| 59 |
Chambolle A, DeVore R A, Lee N Y, et al.. Nonlinear wavelet image processing: variationalproblems, compression, and noise removal through wavelet shrinkage. IEEE Transactions on Image Processing, 1998, 7(3): 319–335.
doi:10.1109/83.661182
|
| 60 |
Combettes P L, Pesquet J C . Wavelet-constrained imagerestoration. International Journal of Wavelets,Multiresolution and Information Processing, 2004, 2(4): 371–389.
doi:10.1142/S0219691304000688
|
| 61 |
Combettes P L . Convex multiresolution analysis. IEEETransactions on Pattern Analysis And Machine Intelligence, 1998, 20(12): 1308–1318.
doi:10.1109/34.735804
|
| 62 |
Liao Z, Tang Y Y . Signal denoising using waveletsand block hidden markov model. InternationalJournal of Pattern Recognition and Artificial Intelligence, 2005, 19(5): 681–700.
doi:10.1142/S0218001405004265
|
| 63 |
You X, Chen Q, Fang B, et al.. Thinning character using modulus minima of wavelettransform. International Journal of PatternRecognition and Artificial Intelligence, 2006, 20(3): 361–376.
doi:10.1142/S0218001406004764
|
| 64 |
Mallat S, Zhong S . Characterization of signalsfrom multiscale edges. IEEE Transactionson Pattern Analysis and Machine Intelligence, 1992, 14(7): 710–732.
doi:10.1109/34.142909
|
| 65 |
Tang Y Y, Yang L H, Feng L . Characterization and detection of edges by Lipschitzexponent and MASW wavelet transform. In: Proc. the 14th Int. Conf. on Pattern Recognition, Brisbane, Australia, August 1998, 1572–1574
|
| 66 |
Hsieh J W, Liao H M, Ko M T, et al.. Wavelet-based shape form shading. Graphical Models and Image Processing, 1995, 57(4): 343–362.
doi:10.1006/gmip.1995.1030
|
| 67 |
Tang Y Y, Cheng H D, Suen C Y . Transformation-ring-projection (TRP) algorithm and itsVLSI implementation. International Journalof Pattern Recognition and Artificial Intelligence, 1991, 5(1 and 2): 25–56.
doi:10.1142/S0218001491000053
|
| 68 |
Horn B K P, Brooks M J, eds. Shape from Shading. Cambridge, MA: MIT Press, 1989
|
| 69 |
Unser M, Aldroubi A, Eden M . On the asymptotic convergence of B-spline wavelets toGabor functions. IEEE Transactions on InformationTheory, 1992, 38: 864–872.
doi:10.1109/18.119742
|
| 70 |
Unser M, Aldroubi A, Eden M . A family of polynomial spline wavelets transforms. Signal Processing, 1993, 30: 141–162.
doi:10.1016/0165‐1684(93)90144‐Y
|
| 71 |
Bow S T . Pattern Recognition and Image Preprocessing. New York: Marcel-Dekker, 1992
|
| 72 |
Shensa M J . The discrete wavelets transform: wedding the atrous and Mallat algorithms. IEEE Transactions Signal Processing, 1992, 40: 2464–2482.
doi:10.1109/78.157290
|
| 73 |
Starck J L, Bijaoui A, Murtagh F . Multiresolution support applied to image filtering anddeconvolution. Graphical Models Image Processing, 1995, 57: 420–431.
doi:10.1006/gmip.1995.1036
|
| 74 |
Tang Y Y, Suen C Y, Yan C D . Document processing for automatic knowledge acquisition. IEEE Transactions on Knowledge and Data Engineering, 1994, 6(1): 3–21.
doi:10.1109/69.273022
|
| 75 |
Mallat S G . Multifrequency channel decompositions of images and wavelet models. IEEE Transactions on Acoust. Speech Signal Process., 1989, 37(12): 2091–2110.
doi:10.1109/29.45554
|
| 76 |
Nastar C, Ayache N . Frequency-based non-rigidmotion analysis. IEEE Transactions on PatternAnal. and Mach. Intell., 18(11), 1996
|
| 77 |
O'Toole A, Abdi H, Deffenbacher K, et al.. Low-dimensional representation of faces in higherdimensions of the face space. Journal ofThe Optical Society of America A., 1993, 10(3): 405–411
|
| 78 |
Sirovich L, Kirby M . Low-dimensional procedurefor the characterization of human faces. Journal of The Optical Society of America A., 1987, 4(3): 519–524
|
| 79 |
Swets D L, Weng J . Using discriminant eigenfeaturesfor image retrieval. IEEE Transactionson Pattern Analysis And Machine Intelligence, 1996, 18(8): 831–836.
doi:10.1109/34.531802
|
| 80 |
Turk M, Pentland A . Eigenfaces for recognition. Journal of Cognitive Neuroscience, 1991, 3(1): 71–86.
doi:10.1162/jocn.1991.3.1.71
|
| 81 |
Yuen P C, Dai D Q, Feng G C . Wavelet-based PCA for human face recognition. Proceeding of IEEE Southwest Symposium on ImageAnalysis and Interpretation, 1998, 223–228
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
