Wavelet theory approach to pattern recognition / Yuan Yan Tang.

Includes bibliographical references (pages 451-459) and index.

ch. 1. Introduction. 1.1. Wavelet : a novel mathematical tool for pattern recognition. 1.2. Brief review of pattern recognition with wavelet theory -- ch. 2. Continuous wavelet transforms. 2.1. General theory of continuous wavelet transforms. 2.2. The continuous wavelet transform as a filter. 2.3. Characterization of Lipschitz regularity of signal by wavelet. 2.4. Some examples of basic wavelets -- ch. 3. Multiresolution analysis and wavelet bases. 3.1. Multiresolution analysis. 3.2. The construction of MRAs. 3.3. The construction of biorthonormal wavelet bases. 3.4. S. mallat algorithms -- ch. 4. Some typical wavelet bases. 4.1. Orthonormal wavelet bases. 4.2. Nonorthonormal wavelet bases -- ch. 5. Step-edge detection by wavelet transform. 5.1. Edge detection with local maximal modulus of wavelet transform. 5.2. Calculation of W[symbol]f(x) and W[symbol]f(x, y). 5.3. Wavelet transform for contour extraction and background removal -- ch. 6. Characterization of dirac-edges with quadratic spline wavelet transform. 6.1. Selection of wavelet functions by derivation. 6.2. Characterization of dirac-structure edges by wavelet transform. 6.3. Experiments -- ch. 7. Construction of new wavelet function and application to curve analysis. 7.1. Construction of new wavelet function -- Tang-Yang wavelet. 7.2. Characterization of curves through new wavelet transform. 7.3. Comparison with other wavelets. 7.4. Algorithm and experiments -- ch. 8. Skeletonization of ribbon-like shapes with new wavelet function. 8.1. Tang-Yang wavelet function. 8.2. Characterization of the boundary of a shape by wavelet transform. 8.3. Wavelet skeletons and its implementation. 8.4. Algorithm and experiment -- ch. 9. Feature extraction by wavelet sub-patterns and divider dimensions. 9.1. Dimensionality reduction of two-dimensional patterns with ring-projection. 9.2. Wavelet orthonormal decomposition to produce sub-patterns. 9.3. Wavelet-fractal scheme. 9.4. Experiments -- ch. 10. Document analysis by reference line detection with 2-D wavelet transform. 10.1. Two-dimensional MRA and mallat algorithm. 10.2. Detection of reference line from sub-images by the MRA. 10.3. Experiments -- ch. 11. Chinese character processing with B-spline wavelet transform. 11.1. Compression of Chinese character. 11.2. Enlargement of type size with arbitrary scale based on wavelet transform. 11.3. Generation of Chinese type style based on wavelet transform -- ch. 12. Classifier design based on orthogonal wavelet series. 12.1. Fundamentals. 12.2. Minimum average lose classifier design. 12.3. Minimum error-probability classifier design. 12.4. Probability density estimation based on orthogonal wavelet series.

The 2nd edition is an update of the book Wavelet Theory and its Application to Pattern Recognition published in 2000. Three new chapters, which are research results conducted during 2001-2008, are added. The book consists of three parts - the first presents a brief survey of the status of pattern recognition with wavelet theory; the second contains the basic theory of wavelet analysis; the third includes applications of wavelet theory to pattern recognition. The new book provides a bibliography of 170 references including the current state-of-the-art theory and applications of wavelet analysis to pattern recognition.

Print version record.

Use copy Restrictions unspecified star MiAaHDL

Electronic reproduction. [Place of publication not identified] : HathiTrust Digital Library, 2011. MiAaHDL

Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. MiAaHDL

http://purl.oclc.org/DLF/benchrepro0212

digitized 2011 HathiTrust Digital Library committed to preserve pda MiAaHDL

eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - Worldwide