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Empirical Wavelet Transform;Stationary and Nonstationary Signals

Journal of Electronic & Information Systems 2019年第2期1卷 1-5页

作者： Hesam Akbari sedigheh ghofrani Biomedical Engineering Department South Tehran BranchIslamic Azad UniversityTehranIran Electrical Engineering Department South Tehran BranchIslamic Azad UniversityTehranIran

Signal decomposition into the frequency components is one of the oldest challenges in the digital signal *** early nineteenth century,Fourier transform(FT)showed that any applicable signal can be decomposed by unlimited ***,the relationship between time and frequency is lost under using *** to many researches for appropriate time-frequency representation,in early twentieth century,wavelet transform(WT)was *** is a well-known method which developed in order to decompose a signal into frequency *** contrast with original WT which is not adaptive according to the input signal,empirical wavelet transform(EWT)was *** this paper,the performance of discrete WT(DWT)and EWT in terms of signal decomposing into basic components are *** this purpose,a stationary signal including five sinusoids and ECG as biomedical and nonstationary signal are *** to being non-adaptive,DWT may remove signal components but EWT because of being adaptive is *** can also extract the baseline of ECG signal easier than DWT.

关键词： Empirical wavelet transform Discrete wavelet transform Signal decomposition

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An Efficient Method for Vehicle License Plate Detection in Complex Scenes

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Circuits and Systems 2011年第4期2卷 320-325页

作者： Mahmood Ashoori Lalimi sedigheh ghofrani 不详

In this paper, we propose an efficient method for license plate localization in the images with various situations and complex background. At the first, in order to reduce problems such as low quality and low contrast in the vehicle images, image contrast is enhanced by the two different methods and the best for following is selected. At the second part, vertical edges of the enhanced image are extracted by sobel mask. Then the most of the noise and background edges are removed by an effective algorithm. The output of this stage is given to a morphological filtering to extract the candidate regions and finally we use several geometrical features such as area of the regions, aspect ratio and edge density to eliminate the non-plate regions and segment the plate from the input car image. This method is performed on some real images that have been captured at the different imaging conditions. The appropriate experimental results show that our proposed method is nearly independent to environmental conditions such as lightening, camera angles and camera distance from the automobile, and license plate rotation.

关键词： License Plate Detection Image Enhancement Background And Noise Removing Morphological Operations

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