This paper extends the technique used for Document Text Extraction from Images using 2-D Haar Wavelet. The discrete wavelet transform is a very useful tool for signal analysis and image processing, especially in multi-resolution representation. It can decompose signal into different components in the frequency domain. Two-dimensional discrete wavelet transform (2-D DWT) decomposes an input imag...

This paper presets a method including a combination of the wavelet transform and fuzzy function approximation (FFA) for high impedance fault (HIF) detection in distribution electricity network. Discrete wavelet transform (DWT) has been used in this paper as a tool for signal analysis. With studying different types of mother signals, detail types and feeder signal, the best case is selected. The...

Wavelets provide an orthonormal basis for multiresolution analysis and decorrelation or 'whitening' of nonstationary time series and spatial processes. Wavelets are particularly well suited to analysis of biological signals and images, such as human brain imaging data, which often have fractal or scale-invariant properties. We briefly define some key properties of the discrete wavelet transform...

The Discrete Wavelet Transform (DWT) has been applied to data compression to decorrelate the data and concentrate the energy in a small portion of the coefficients. Compression can be achieved since most of the quantized wavelet coefficients are zeros. For the decoder, the traditional inverse discrete wavelet transform (IDWT) has a complexity proportional to the size of the data. In this paper,...

The discrete wavelet transform (DWT) algorithms have a firm position in multi-scale processing of biomedical signals, such as EMG and EEG. The DWT algorithms were initially based on the compactly supported conjugate quadrature filters (CQFs) (Smith & Barnwell, 1986; Daubechies, 1988). However, a drawback in CQFs is due to the nonlinear phase effects such as spatial dislocations in multi-scale a...

In this paper, we study the problem of compressing a signal buried in additive white Gaussian noise. The approach we propose is to design an asymptotically optimal quantizer in the the wavelet domain. The undecimated discrete wavelet transform is shift-invariant and redundant, thus it is robust compared with the decimated and orthogonal discrete wavelet transform (DWT). Compared with the origin...

An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are...

Induction motors need to be monitored regularly because it involves the company's productivity. The induction motor monitoring method in this study uses a current variable which is transformed using Discrete Wavelet Transform. Transform (DWT) used results are satisfactory for detecting short circuit stator winding of an motor. Of many types and levels discrete wavelet transforms, haar transform...

The influence of the number of Discrete Wavelet Transform (DWT) iterations on a wavelet OFDM (WOFDM) system performance is studied in this paper. The WOFDM transmission is tested on a flat, time variant radio channel. Basically, the number of DWT iterations coincides with the number of transmission scales used. Our simulations show that by increasing the value of this parameter, the BER perform...

The Discrete Wavelet Transform (DWT) has gained the reputation of being a very effective signal analysis tool for many practical applications. This paper presents an approach towards VLSI implementation of the Discrete Wavelet Transform for image compression. The design conforms to JPEG2000 standard and can be used for both lossy and lossless compression. In Discrete Wavelet transform, the filt...