Sharif Digital Repository

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...