A new corner detection method for contour images is proposed based on dyadic wavelet transform (WT) at local natural scales. The points corresponding to wavelet transform modulus maxima (WTMM) at different scales are taken as corner candidates. For each candidate, the scale at which the maximum value of the normalized WTMM exists is defined as its ‘‘local natural scale’’, and the corresponding ...

This paper presents the experimental pilot study to investigate the effects of pulsed electromagnetic field (PEMF) at extremely low frequency (ELF) in response to photoplethysmographic (PPG), electrocardiographic (ECG), electroencephalographic (EEG) activity. The assessment of wavelet transform (WT) as a feature extraction method was used in representing the electrophysiological signals. Consid...

introduction: evoked potentials arisen by stimulating the brain can be utilized as a communication tool  between humans and machines. most brain-computer interface (bci) systems use the p300 component,  which is an evoked potential. in this paper, we evaluate the use of the hidden markov model (hmm) for  detection of p300.  materials and methods: the wavelet transforms, wavelet-enhanced indepen...

The Wormhole attack is a critical and challenging security threat for wireless sensor networks (WSNs). Although launching a wormhole attack is a relatively trivial task for the attacker, detecting it from an infected WSN is a tough job, because it can be launched from a compromised legitimate node. In recent years, signal processing methods, like the short term Fourier transform (STFT) and wave...

Electroencephalograms (EEGs) are brain waves, which are recorded using scalp electrodes. Generally, signal attenuate on recording and amplitude of the evoked potentials (EPs) are low when merged with the base brain waves. Therefore, mathematical tools are needed to analysis the time series (EEGs) to discover the EPs in the base EEGs. This paper reviews spectral analysis based on periodic amplit...

abstract background: a computer aided diagnosis system was established using the wavelet transform and neural network to differentiate malignant from benign in a   group of patients with histo-pathologically proved breast lesions based on the data derived independ­ently from time-intensity profile.   materials and methods: the per­formance of the artificial neural network (ann) was evaluated us...

Methods: This study investigates multiscale texture features extracted from CRC pathology sections using 3D wavelet transform (3D-WT) filter. Multiscale features were extracted from digital whole slide images of 39 patients that were segmented in a pre-processing step using an active contour model. The capacity for multiscale texture to compare and classify between PTs was investigated using AN...

The aim of this paper is to examine a set of wavelet functions (wavelets) used in image watermarking system. Several wavelet functions are used to transform the component detail of the image in frequency domain. Discrete wavelet transform (DWT), discrete Fourier transform (DFT) and discrete cosine transform (DCT) are some commonly used transform domain functions out of which discrete wavelet tr...

introduction: an efficient method of tomographic imaging in nuclear medicine is positron emission tomography (pet). compared to spect, pet has the advantages of higher levels of sensitivity, spatial resolution and more accurate quantification. however, high noise levels in the image limit its diagnostic utility. noise removal in nuclear medicine is traditionally based on fourier decomposition o...

there are two methods for identifying formation interface in oil wells: core analysis, which is a precise approach but costly and time consuming, and well logs analysis, which petrophysists perform, which is subjective and not completely reliable. in this paper, a novel coupled method was proposed to detect the formation interfaces using gr logs. second approximation level (a2) of gr log gained...