Palmprint is a physiological biometric trait and is efficient in identifying a person. In this paper we propose Palmprint Identification based on fusion of KWT and DWT at matching Score level (PIFKDM). The palmprint image is preprocessed to generate histogram equalized ROI. The KWT and DWT are applied on preprocessed image. The KWT coefficients and LL band of DWT are considered as features. The...

In order to improve bitrates of lossless JPEG 2000, we propose to modify the discrete wavelet transform (DWT) by skipping selected steps of its computation. We employ a heuristic to construct the skipped steps DWT (SS-DWT) in an image-adaptive way and define fixed SS-DWT variants. For a large and diverse set of images, we find that SS-DWT significantly improves bitrates of non-photographic imag...

The digital data can be transformed using Discrete Wavelet Transform (DWT). The images need to be transformed without loosing of information. The Discrete Wavelet Transform (DWT) was based on time-scale representation, which provides efficient multi-resolution. The lifting based DWT are lower computational complexity and reduced memory requirements. The discrete wavelet transform (DWT) is being...

Parkinson's disease is a recognizable clinical syndrome with variety of causes and presentations; it represents rapidly growing neurodegenerative disorder. Since about 90 percent sufferers have some form early speech impairment, recent studies on tele diagnosis focused the recognition voice impairments from vowel phonations or subjects' discourse. In this paper, we present new approach for dete...

Objective: Recent advances in development of low-cost single-channel electroencephalography (EEG) headbands have opened new possibilities for applications health monitoring and brain-computer interface (BCI) systems. These recorded EEG signals, however, are often contaminated by eye blink artifacts that can yield the fallacious interpretation brain activity. This paper proposes an efficient alg...

Introduction: Brain visual evoked potential (VEP) signals are commonly known to be accompanied by high levels of background noise typically from the spontaneous background brain activity of electroencephalography (EEG) signals. Material and Methods: A model based on dyadic filter bank, discrete wavelet transform (DWT), and singular value decomposition (SVD) was developed to analyze the raw data...

this paper presents the application of radial basis neural networks to the development of a novel method for the condition monitoring and fault diagnosis of synchronous generators. in the proposed scheme, flux linkage analysis is used to reach a decision. probabilistic neural network (pnn) and discrete wavelet transform (dwt) are used in design of fault diagnosis system. pnn as main part of thi...

In this paper, we propose a novel method for facial feature extraction using the directional multiresolution decomposition offered by the complex wavelet transform. The dual-tree implementation of complex wavelet transform offered by Selesnick is used (DT-DWT(S)) [I.W., Selesnick, R.G. Baraniuk, N.C. Kingsbury, The dual-tree complex wavelet transform, IEEE Signal Processing Magazine, 6, s.l., I...

The main goal of this paper is to embed a watermark in the speech signal, using the three techniques such as Discrete Cosine Transform (DCT) along with Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT).In this paper, various combinations were tried for embedding the watermark image into the audio signal such as DWT and SVD, DCT with SVD and DCT, DWT with SVD. Their perform...