Wavelet Applications in Pattern Recognition

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Piri Pishekloo, Bijan | 2010

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 40372 (02)
University: Sharif University of Technology
Department: Mathematical Sciences
Advisor(s): Mahdavi Amiri, Nezameddin
Abstract:
We study wavelet transformation for use in pattern recognition. Feature extraction is a crucial processing step for pattern recognition. Feature extraction is based on finding mathematical methods for reducing dimensionality of pattern representation. Two most important features to be extracted are edges and textures. Edges and textures are not absolute concepts and change with scale. Moreover, local characteristics of edges are needed. In recent decades, wavelet transformation as a mathematical tool has captured the attention of many scientists in signal processing and mathematics. Wavelet basis can provide efficient and useful description of a function or signal since it has local properties in both time and frequency. Also, wavelets can characterize patterns in different scales by their multiresolution analysis properties. We present different applications of wavelets in pattern recognition and analyze effectiveness of our generated software with several examples
Keywords:
Wavelets ; Feature Extraction ; Edges ; Textures ; Pattern Recognition

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