Wavelets for Multiresolution Shape Recognition

This paper describes a new method for 2-D shape recognition based on a multiresolution characterisation of the shape. From the Wavelet coefficients, features are extracted in order to perform a translation-rotation-scaling invariant recognition. Wavelets and multiresolution are exploited in order to reduce complexity of the matching task between the input image and the set of models. In the paper, motivations and performance of the algorithm are presented. Experimental results are also reported in several tests, including noise addition. The approach is quite general, and it could be extended to texture analysis, thus providing a unified paradigm for shape and texture recognition.

[1]  I. Daubechies.  Orthonormal bases of compactly supported wavelets , 1988 .

[2]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.

[4]  Edward H. Adelson,et al.  The Laplacian Pyramid as a Compact Image Code , 1983, IEEE Trans. Commun..

[5]  John D. Villasenor,et al.  Visual thresholds for wavelet quantization error , 1996, Electronic Imaging.

[6]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[7]  Yuan Yan Tang,et al.  Multiresolution recognition of unconstrained handwritten numerals with wavelet transform and multilayer cluster neural network , 1996, Pattern Recognit..

[8]  C. Sidney Burrus,et al.  Nonlinear processing of a shift-invariant discrete wavelet transform (DWT) for noise reduction , 1995, Defense, Security, and Sensing.

[9]  Carlo Arcelli,et al.  Sketching a grey-tone pattern from its distance transform , 1996, Pattern Recognit..

[10]  I. Daubechies,et al.  Biorthogonal bases of compactly supported wavelets , 1992 .

[11]  Silvia Bertoluzza,et al.  Coupling of human visual system model and wavelet transform for image compression , 1994, Optics & Photonics.

[12]  A. Haar.  Zur Theorie der orthogonalen Funktionensysteme , 1910 .

[13]  Stéphane Mallat,et al.  Multifrequency channel decompositions of images and wavelet models , 1989, IEEE Trans. Acoust. Speech Signal Process..

[14]  Jelena Kovacevic,et al.  Wavelets and Subband Coding , 2013, Prentice Hall Signal Processing Series.

[15]  Jerome M. Shapiro,et al.  An embedded hierarchical image coder using zerotrees of wavelet coefficients , 1993, [Proceedings] DCC `93: Data Compression Conference.

[16]  Albert Bijaoui,et al.  A multiscale vision model applied to astronomical images , 1996 .

[17]  Gordon W. Roberts,et al.  A BIST scheme for a SNR, gain tracking, and frequency response test of a sigma-delta ADC , 1995 .

[18]  Chen-Huei Chiang,et al.  Wavelets and perfect reconstruction subband coding with causal stable IIR filters , 1995 .

[19]  Yuichi Nakamura,et al.  Learning two-dimensional shapes using wavelet local extrema , 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 2 - Conference B: Computer Vision & Image Processing. (Cat. No.94CH3440-5).

[20]  Fabrizio Argenti,et al.  Source Coding and Transmission of HDTV Images Compressed with the Wavelet Transform , 1993, IEEE J. Sel. Areas Commun..