Wavelet Transforms and Their Applications in Biology and Geoscience

308 Pages·2016·22.08 MB·English

by  Baleanu D. (Ed.)

WAVELET TRANSFORMS
AND THEIR RECENT
APPLICATIONS IN BIOLOGY
AND GEOSCIENCE

Edited by Dumitru Baleanu
Wavelet Transforms and Their Recent Applications in Biology and Geoscience
Edited by Dumitru Baleanu

Published by InTech
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Copyright © 2012 InTech
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First published February, 2012
Printed in Croatia

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Contents

Preface IX
Part 1 Wavelet Transforms in Biology 1
Chapter 1 Wavelet Transform
for the Analysis of EEG Signals
in Patients with Oral Communications Problems 3
Maria Viqueira, Begona García Zapirain,
Amaia Mendez Zorrilla and Ibon Ruiz
Chapter 2 Energy Distribution of EEG
Signal Components by Wavelet Transform 45
Ibrahim Omerhodzic, Samir Avdakovic,
Amir Nuhanovic, Kemal Dizdarevic and Kresimir Rotim
Chapter 3 Using Wavelet Transforms for Dimensionality
Reduction in a Gait Recognition Framework 61
Milene Arantes and Adilson Gonzaga
Chapter 4 The Detection Data of
Mammary Carcinoma Processing
Method Based on the Wavelet Transformation 77
Meng Yao, Zhifu Tao and Zhongling Han
Chapter 5 Wavelet Transforms in Sport:
Application to Biological Time Series 93
Juan Manuel Martín-González and Juan Manuel García-Manso
Chapter 6 2-D Discrete Wavelet Transform for Hand
Palm Texture Biometric Identification and Verification 103
Juan José Fuertes Cebrián,
Carlos Manuel Travieso González and Valery Naranjo Ornedo
Chapter 7 Brain Computer Interface with
Wavelets and Genetic Algorithms 119
Abdolreza Asadi Ghanbari, Mir Mohsen Pedram, Ali Ahmadi,
Hamidreza Navidi, Ali Broumandnia and Seyyed Reza Aleaghil
VI Contents

Chapter 8 Improvement of Shimmer Parameter
of Oesophageal Voices Using Wavelet Transform 139
Ibon Ruiz and Begoña García Zapirain
Chapter 9 Poisson Noise Removal in Spherical
Multichannel Images: Application to Fermi Data 161
Jérémy Schmitt, Jean-Luc Starck, Jalal Fadili and Seth Digel
Chapter 10 A Wavelet Multiscale De-Noising
Algorithm Based on Radon Transform 189
Xueling Zhu, Xiaofeng Yang, Qinwu Zhou,
Liya Wang, Fulai Yuan and Zhengzhong Bian
Chapter 11 Application of Wavelet Transform
Method for Textile Material Feature Extraction 207
Lijing Wang, Zhongmin Deng and Xungai Wang
Chapter 12 Wavelet Transform-Multidisciplinary Applications 225
Ali Al-Ataby, Waleed Al-Nuaimy and Mohammed A. M. Abdullah
Part 2 Applications of the Wavelet Transforms in Geoscience 251
Chapter 13 Multiscale Analysis of Geophysical Signals
Using the 2D Continuous Wavelet Transform 253
Sid-Ali Ouadfeul, Leila Aliouane,
Mohamed Hamoudi, Amar Boudella and Said Eladj
Chapter 14 1D Wavelet Transform and Geosciences 277
Sid-Ali Ouadfeul, Leila Aliouane,
Mohamed Hamoudi, Amar Boudella and Said Eladj

Preface

Wavelet analysis is one of the most effective solutions to overcome the drawbacks of
Fourier analysis, and since the seminal work of Ingrid Daubechies was published in
the late 1980s, it has been applied very successfully in various branches of science and
engineering. The fractional wavelet techniques started to play an important role in
data treatment corresponding to complex systems during the last decade.
The wavelet transform and it generalization started to be an efficient mathematical
tool which has been widely used to investigate a signal in a time-frequency
representation to allow analyzing the parts of interest individually.
As it is well known the main difficulty in processing the biological signals is their
extreme variability and the requirement to analyse on a case by case basis. The wavelet
transform is recognized as an useful tool in the signal analysis corresponding to the
biological data as well as to the complex seismic data.
This book aims to show the range of applications of wavelet analysis to data from the
field of biology and geosciences.
Specifically, the book contains chapters showing how the wavelet transform was used
for the analysis of EEG signals in patients with oral communications,how it was used
to investigate the energy distribution of the EEG signal components as well as its use
for the dimensional reduction in a gait recognition framework.
One of the chapters shows how we can convert EEG activity into cursor movement by
a brain computer interface using an appropriate feature extraction scheme. The
detection data of mammary carcinoma processing method based on the wavelet
transformation was presented. The applications of the wavelet method in sport and
hand palm texture biometric identification and verification were illustrated.
Improvement of shimmer parameter of oesophageal voices using wavelet transform
and the application of this method for textile material feature extraction is another
interesting topic covered by this book. The powerful utilization of the wavelet
transform and its varieties in two important applications, namely biometrics and non-
destructive testing is explained in detail.
X Preface

In this book the reader can find new methods involving two spherical multiscale
transforms, the wavelet and the curvelets, and the design for restoration of spherical
data with noise following a Poisson distribution.
The book ends with two applications of 1D and 2D wavelet transforms used in
treatments of the geophysical signals.
I strongly believe that the chapters of this book will be of great help for graduate and
postgraduate students, as well as for researchers who will get a general view of the
powerful wavelet method and its applications in treatment of biological and
geoscience data .

Dumitru Baleanu
Cankaya University, Faculty of Art and Sciences,
Department of Mathematics and Computer Sciences, Ankara,
Turkey

Institute of Space Sciences, Magurele-Bucharest,
Romania