scholarly journals Wearable Technology: Signal Recovery of Electrocardiogram from Short Spaced Leads in the Far-field Using Discrete Wavelet Transform Based Techniques

2019 ◽  
Author(s):  
Niamh McCallan ◽  
Dewar Finlay ◽  
Pardis Biglarbeigi ◽  
Gilberto Perpiñan ◽  
Michael Jennings ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Wearable Technology ◽  
Discrete Wavelet ◽  
Signal Recovery ◽  
Far Field

scholarly journals Detection of artifacts in the EEG signal with using wavelet transform

2011 ◽  
Vol 16 (4) ◽  
pp. 126-130
Author(s):  
A.A. Popov ◽  
A.M. Kanajkin ◽  
K.A. Roshchina ◽  
O.R. CHertov ◽  
V.A. SHashkov
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Signal Recovery ◽  
Eeg Signal

The paper considers the task of cleaning up the EEG signal from artifacts. Method for identifying electrooculogram and signal recovery after its removal using discrete wavelet transform of the electroencephalogram is proposed. The developed method showed nice results on examined examples of real signals at localization and removal of artifacts

Improving Space Localization Properties of the Discrete Wavelet Transform

Informatica ◽  
2013 ◽  
Vol 24 (4) ◽  
pp. 657-675
Author(s):  
Jonas Valantinas ◽  
Deividas Kančelkis ◽  
Rokas Valantinas ◽  
Gintarė Viščiūtė
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Space Localization

An Adaptive Binarization Method for Cost-efficient Document Image System in Wavelet Domain

2020 ◽  
Vol 64 (3) ◽  
pp. 30401-1-30401-14 ◽  
Author(s):  
Chih-Hsien Hsia ◽  
Ting-Yu Lin ◽  
Jen-Shiun Chiang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Document Image ◽  
Background Information ◽  
Raspberry Pi ◽  
Discrete Wavelet ◽  
Image System ◽  
Low Frequencies ◽  
Cost Efficient ◽  
Binarization Method

Abstract In recent years, the preservation of handwritten historical documents and scripts archived by digitized images has been gradually emphasized. However, the selection of different thicknesses of the paper for printing or writing is likely to make the content of the back page seep into the front page. In order to solve this, a cost-efficient document image system is proposed. In this system, the authors use Adaptive Directional Lifting-Based Discrete Wavelet Transform to transform image data from spatial domain to frequency domain and perform on high and low frequencies, respectively. For low frequencies, the authors use local threshold to remove most background information. For high frequencies, they use modified Least Mean Square training algorithm to produce a unique weighted mask and perform convolution on original frequency, respectively. Afterward, Inverse Adaptive Directional Lifting-Based Discrete Wavelet Transform is performed to reconstruct the four subband images to a resulting image with original size. Finally, a global binarization method, Otsu’s method, is applied to transform a gray scale image to a binary image as the output result. The results show that the difference in operation time of this work between a personal computer (PC) and Raspberry Pi is little. Therefore, the proposed cost-efficient document image system which performed on Raspberry Pi embedded platform has the same performance and obtains the same results as those performed on a PC.

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